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"}}},{"metadata":{},"cell_type":"markdown","source":"# Table of Content"},{"metadata":{},"cell_type":"markdown","source":"Welcome to this beginner friendly guide to **object detection** using **EfficientDet**. Similarly to what I have done in the NLP guide (check it [here](https://www.kaggle.com/yassinealouini/roberta-meets-tpus) if you haven't yet already), there \nwill be a mix of **theory**, **practice**, and an **application** to the [global wheat competition dataset](https://www.kaggle.com/c/global-wheat-detection). \n\n\n\nThis will be a very long notebook, so use the following table of content if necessary. Grab something to drink and enjoy!\n\n- [Introduction](#intro)\n- [Modern Computer Vision](#modern-cv) \n * [Different Detection Tasks](#different-tasks)\n * [Object Detection 101](#od-101)\n * [Object Detection Models Zoology](#od-zoology)\n- [EfficientDet Explained](#efficientdet)\n * [EfficientNet as a Backbone](#\"effnet-backbone\")\n * [BiFPN as a Multi-Scale Fusion](#bifpn)\n * [Two Heads](#heads)\n * [Compound Scalings](#scalings)\n- [Application: Global Wheat Detection](#application)\n * [Understanding the Task](#understanding)\n * [Evaluation Metric](#evaluation-metric)\n * [Data processing](#processing)\n * [The Model](#model)\n * [The Dataset](#dataset)\n * [Pytorch Complete Training Pipeline](#pipeline)\n * [Evaluation](#evaluation)\n * [Inference](#inference)\n \n- [Advanced Concepts](#advanced)\n * [Mosaic Augmentation](#augmentation)\n * [TTA](#tta)\n * [WBF](#wbf)\n \n- [To Wrap up](#wrap-up)\n- [To Go Beyond](#going-beyond)\n\n\nOne last thing before I start, I have benefited immensely from the following two notebooks: \n\n- A Pytorch Lightning end-to-end training [pipeline](https://www.kaggle.com/artgor/object-detection-with-pytorch-lightning) by the great [Andrew Lukyanenko](https://www.kaggle.com/artgor). There is a Github [repo](https://github.com/Erlemar/wheat) as well if you want better organised code. If youy don't know who Andrew \"artgor\" is, now is the time to discover lots of cool notebooks. ;)\n\n- A Pytorch (no Lightning this time) end-to-end training [pipeline](https://www.kaggle.com/shonenkov/training-efficientdet) by the great  [Alex Shonenkov](https://www.kaggle.com/shonenkov). Check his work, he has many other great CV notebooks.\n\nWith these shoutouts out of the way, let's start."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"intro\"></a>\n# Introduction "},{"metadata":{},"cell_type":"markdown","source":"Computer vision went through a fast cycle of innovations and improvements starting in **2012** with \nthe [AlexNet](https://en.wikipedia.org/wiki/AlexNet) network revolution.\n\nIndeed, this was according to many one of the moments that launched again the field of deep learning from the last [\"AI winter\"](https://en.wikipedia.org/wiki/AI_winter): for the first time, it was possible to train neural networks unsing **large dataset**s and **lots of compute** (well according to 2012's standards anyway :p).\n\nThis is what made the model achive state of the art performance on [ImageNet](http://www.image-net.org/). Indeed, it has achieved in 2012 a **top-5 error of 15.3%** which was 10% better than pervious year's performance (the lower, the better). \n\nSo, what does this network contain?\n\nThe **AlexNet** network is quite simple: different **[CNN](https://cs231n.github.io/convolutional-networks/)** layers followed by max-pooling then a fully-connected layer. \n\nFast forward to 2020, a lot of things happened and the performances kept improving year after year: ImageNet is now considered a \"solved\" (kind of in most cases at least) dataset. In fact, it has been solved since at least **2015** with the introduction of the [**ResNet**](https://en.wikipedia.org/wiki/Residual_neural_network) model, i.e. getting performance better than human-level for the first time (see the graph below). \n\n\n\n<img src=\"https://i0.wp.com/semiengineering.com/wp-content/uploads/2019/10/Synopsys_computer-vision-processors-EV7-Fig2-ImageNet.jpeg?w=640&ssl=1\">\n\n\nSource: https://semiengineering.com/new-vision-technologies-for-real-world-applications/\n\nTo read more about what happened over the last years in the field of deep learning, check the following [blog post](https://adeshpande3.github.io/adeshpande3.github.io/The-Last-5-Years-in-Deep-Learning)\n\nMost of these systems share similar architectures and modern \"tips\" to make them work best.\n\nIn what follows, I will detail some of what makes the modern computer vision ecosystem.\n\nHere we go!"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"modern-cv\"></a>\n# Modern Computer Vision "},{"metadata":{},"cell_type":"markdown","source":"Before focusing on **object detection**, let's move one step back and explore the modern computer vision landscape. \n\nThe first step was making CNNs work: that's roughly what happened around 2012 and has been improved ever since as discussed in the previous section. \n\nThen, the idea was to make the networks deeper to get better performances. Two main problems appeared then: \n\n1. networks got too many parameters\n2. convergence wasn't fast or happening at all\n\nTo solve these issues, few interesting ideas were introduced. As stated by Karpathy in one talk (haven't found the link yet, if you know it, please share in the comments): \"more zeros, better performance\". What does that mean? In short, more 0s everywhere in the network: \n\n- Max-pooling instead of average pooling\n- ReLU layer\n- Dropout \n\nThus less parameters.\n\nSomething else happened: **code discovery**, **sharing**, and **reproducibility** got better. I don't have \nany data to back this claim but that's what I have observed through experience. For instance, [papers with code](https://paperswithcode.com/) is probably the best place to look for a code implementation.\n\nAlso, the **code ecosystem** got much better. Among the recent code libraries and tools: \n\n- [Pytorch](https://pytorch.org/) and the [torchvision](https://pytorch.org/docs/stable/torchvision/index.html) library particularly for computer vision tasks\n- [Pytorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning) for easier training\n- [Fastai](https://www.fast.ai/) and its CV module for an intrigated experience with latest CV best practices.\n\nFinally, some of the recent research trends:\n\n- more efficient architectures, i.e. even less parameters. More on this in the following sections.\n- automated neural architecture search\n- transfer learning\n- application of attention ideas from the recent NLP progress. Check this blog [post](https://towardsdatascience.com/self-attention-in-computer-vision-2782727021f6) for some details.\n\nAll these things make the modern-days computer vision ecosystem. Let's now move to the subfield of **object detection**."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"different-tasks\"></a>\n\n## Different Detection Tasks"},{"metadata":{},"cell_type":"markdown","source":"We will mainly focus on **three** similar **detection tasks** (from simpler to more complex):\n    \n- object detection\n- semantic segmentation\n- instance segmentation\n\nObject detection is the easiest one. It consists in placing bounding boxes around detected objects. The two remaining tasks are best described in the image below:\n\n<img src=\"https://i.stack.imgur.com/MEB9F.png\">\n\nSource: https://datascience.stackexchange.com/questions/52015/what-is-the-difference-between-semantic-segmentation-object-detection-and-insta\n\n\nAll three tasks share the following thing: given an **object** the aim is to **locate** some pixels that identify it: \n\n- for object detection, 4 numbers are predicted (either two corners or  center and width and height, check the figure below for more details) and a label's probability. \n- for semantic segmentation, the countours of each label are predicted (more numbers), i.e. for each pixel predict to which class it belongs.\n- for instance segmentation, the instances of each label are predicted (much more numnbers), i.e. for each pixel predict to which class it belongs + its id.\n\n\n![object_detection_bbox.png](attachment:object_detection_bbox.png)\n\n\nThe two most popular ways to annotate a bounding box. Left for the reader: how to move from one to the other?\n\nNow that we are more familiar with the general detection tasks, we can move to **object detection**.   ","attachments":{"object_detection_bbox.png":{"image/png":"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"}}},{"metadata":{},"cell_type":"markdown","source":"<a id=\"od-101\"></a>\n\n## Object Detection 101"},{"metadata":{},"cell_type":"markdown","source":"What is object detection?\n\nFor humans, this is a straightforward question: given an **image** and a **label**, draw a **bounding box** around the detected objects. In other words, it is localization plus classification of objects.\n\nHowever, translating this task into an algorithm is on another level of hard. \nIndeed, where do you even start?\n\n\n![object_detection_explained.png](attachment:object_detection_explained.png)\n\n\nLegend: on top, human perspective. Bottom, computer perspective.\n\n\nI also like this definition from [paperswithcode](https://paperswithcode.com/task/object-detection/latest): \n\n> Object detection is the task of detecting instances of objects of a certain class within an image. The state-of-the-art methods can be categorized into two main types: one-stage methods and two stage-methods. One-stage methods prioritize inference speed, and example models include YOLO, SSD and RetinaNet. Two-stage methods prioritize detection accuracy, and example models include Faster R-CNN, Mask R-CNN and Cascade R-CNN.\nThe most popular benchmark is the MSCOCO dataset. Models are typically evaluated according to a Mean Average Precision metric.\n\n\n\nFortunately, we don't need to really understand what goes inside our brains. It appears that \ndeep learning models are very good at that. Indeed, given the latest [ImageNet](http://www.image-net.org/) and [COCO](https://cocodataset.org/#home) benchmarks, deep learning models are beating human-level performance: that was the case on the ImageNet dataset since 2015 and that's the case for the COCO dataset since . \n\nSo, the next question is: how to design a good neural network for object detection?\n\n\nLet's have a look at the most common techniques to have a feel for what works. From Wikipedia's [object detection](https://en.wikipedia.org/wiki/Object_detection) page: \n    \n* Region Proposals (R-CNN,Fast R-CNN, Faster R-CNN, cascade R-CNN, and so on)\n* Single Shot MultiBox Detector (SSD) \n* You Only Look Once (YOLO) \n* Single-Shot Refinement Neural Network for Object Detection (RefineDet)\n* Retina-Net \n* Deformable convolutional networks\n\nWe can also add **EfficientDet** ;). Well this list isn't very informative, is it? \nBased on my own experience (basically reading a lot of blog posts and papers), there are **two** major families: \n\n- Two steps networks\n- One step networks\n\nR-CNN and its \"cousins\" fall into the first family of models. \nIn contrast to the R-CNN family, SSD, YOLO, RetinaNet, CeneterNet and EfficientDet fall into the faster, one step family. \n\n\nFinally, to learn more about these two families of models, check this [blog post](https://cv-tricks.com/object-detection/faster-r-cnn-yolo-ssd/) and this [slides deck](https://fr.slideshare.net/pfi/a-brief-history-of-object-detection-tommi-kerola) telling a brief history of object detection. \n\nLet's explore further this rich ecosystem of models.","attachments":{"object_detection_explained.png":{"image/png":"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"}}},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","collapsed":true,"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":false},"cell_type":"markdown","source":"<a id=\"od-zoology\"></a>\n\n## Object Detection Models Zoology"},{"metadata":{},"cell_type":"markdown","source":"As stated above, it seems that deep learning models, particularly convolutional ones are very good at image processing tasks, and in particular object detection. We won't explore why this is the case so feel free to explore this subject on your own. One possible explanation is that deep neural networks are good at distilling features from noisy inputs and this can be explained by the \n[information bottleneck theory](https://en.wikipedia.org/wiki/Information_bottleneck_method). \n\nInstead, let's explore some SOTA (state-of-the-art) models and see what they have in common: \n\n\n* **SSD**: [paper](https://arxiv.org/pdf/1512.02325.pdf) and pytorch [implementation]. (https://pytorch.org/hub/nvidia_deeplearningexamples_ssd/). Notice that SSD stands for \"Single Shot MultiBox Detector\".\n\n* **FPN**: [paper](https://openaccess.thecvf.com/content_cvpr_2017/papers/Lin_Feature_Pyramid_Networks_CVPR_2017_paper.pdf) and pytorch [implementation](https://github.com/jwyang/fpn.pytorch). Notice that FPN stands for \"Feature Pyramid Networks\". \n\n* **RetinaNET**: [paper](https://arxiv.org/pdf/1708.02002.pdf) and pytorch [implementation](https://github.com/yhenon/pytorch-retinanet). \n\n* **Mask RCNN**: [paper](https://arxiv.org/pdf/1703.06870.pdf) and pytorch [tutorial](https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html) on how to fine-tune it. Notice that this model is a generalization of [Faster RCNN](https://arxiv.org/abs/1506.01497) that adds instance segmentation on top of object detection. \n\n* **CenterNet**: [paper](https://arxiv.org/pdf/1904.08189.pdf) and pytorch [implementation](https://github.com/xingyizhou/CenterNet).\n\n* **YOLO**: [website](https://pjreddie.com/darknet/yolo/) and v3 [paper](https://pjreddie.com/media/files/papers/YOLOv3.pdf). As the website claims, it is 100 times faster than Mask RCNN. There is even a v5 [now](https://github.com/ultralytics/yolov5). Notice that YOLO stands for \"You Only Look Once\". \n\n* **EfficientDet**: [paper](https://arxiv.org/pdf/1911.09070.pdf) and pytorch [implementation](https://github.com/rwightman/efficientdet-pytorch). \n\n* **DETR**: model detection using the transformer architecture. [paper](https://arxiv.org/abs/2005.12872) and pytorch [implementation](https://github.com/facebookresearch/detr). \n\n\n\nTo dig deeper, here are some more details:\n\n\n* **SSD**\n\n  * SSD is short for single shot detector\n  * As it is clear from its name, it belonges to the one step family\n  * Paper accepted around 2016 (end of)\n  \n  <img src=\"https://paperswithcode.com/media/methods/Screen_Shot_2020-06-27_at_1.59.27_PM.png\" width=480>\n  \n  \n* **FPN**\n\n  * FPN is short for feature pyarmic network\n  * This isn't an object detection network per say but rather a part\n  * It is used in many architecture as the features extraction part\n  * Paper accepted in 2017\n\n* **Mask R-CNN**\n\n  * From the region proposals series of models, this is the latest one\n  * It is an extension of faster r-cnn for instance segmentation\n  * It seems that it gives better results even for object detection\n  * To learn more, read [this](https://medium.com/@jonathan_hui/what-do-we-learn-from-region-based-object-detectors-faster-r-cnn-r-fcn-fpn-7e354377a7c9) blog post and [this](https://paperswithcode.com/method/mask-r-cnn) paperswithcode page.\n\n\n* **RetinaNet**\n\n  * Uses focal loss\n  \n  <img src=\"https://miro.medium.com/max/558/1*FCV96tP679EScoiwKq4IaQ.png\" width=240>\n  \n  * Uses FPN as its features extraction layer \n  \n  <img src=\"https://miro.medium.com/max/1395/1*jQFeF7gj6uCXVzUb08S9lg.png\" width=480>\n\n* **CenterNet**\n\n  * Paper accepted in 2019\n  * Estimates the center of the bounding box in addition to the corners\n  * Belongs to the one stage family of models \n  * Claims to have the best performance for the one stage family and not very far from the best in two stages as well\n  * Has two networks: one for finding the center and one for finding the corners\n  * As usual, to learn more check the paperswithcode [page](https://paperswithcode.com/method/centernet)\n  \n  <img src=\"https://paperswithcode.com/media/methods/Screen_Shot_2020-06-23_at_12.29.21_PM_bAPb2Mm.png\" width=480>\n\n* **YOLO**\n\n  * Uses a different format for the outputted bounding box: the center + width and height instead of top-left and bottom-right corners. \n  * Among the one stage family of models\n  * Fast predictions with great mAP\n  * Latest versions use FPN as a features extracting layer\n  * Has been through many iterations (latest being v4). If you want a very complete blog post, check this [one](https://medium.com/@jonathan_hui/yolov4-c9901eaa8e61) and the [paperswithcode](https://paperswithcode.com/method/yolov4) page. \n  * V4  paper accepted in 2020\n  \n  <img src=\"https://paperswithcode.com/media/methods/new_ap.jpg\" width=480>\n\n\n\n* **EfficientDet**\n\n  * Originally developed by the google brain team using architecture search. \n  * The original accompanying code could be found [here](https://github.com/google/automl/tree/master/efficientdet) \n  * A great [notebook](https://www.kaggle.com/shonenkov/training-efficientdet/notebook) to get started training an EfficientDet model on this competition dataset. Thanks to [Alex Shonenkov](https://www.kaggle.com/shonenkov). \n  * To get the backbon weights, go to the [README](https://github.com/rwightman/efficientdet-pytorch/blob/master/README.md#models) page, models section, where you can find this table and click on the weights you want\n\n     <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2Ff93c2555f13dbf00aa02ee5af5802b51%2Feffdet_weights.png?generation=1595103664975637&amp;alt=media\" width=480>\n  \n  * COCO AP (average precision) vs FLOPS (number of operations per second) graph:\n\n    <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2F694e635d898de75b2a968ceb17fd9fde%2Fcoco_ap_vs_flops.png?generation=1595096249664191&amp;alt=media\" width=480>\n\n\n  * SOTA according to [paperwithcode](https://paperswithcode.com/paper/efficientdet-scalable-and-efficient-object). Here is graph that shows that EfficientDet-D7x (largest model) achieves it on the COCO object detection benchmark:\n  \n     ![coco_object_detection_score.png](attachment:coco_object_detection_score.png)\n \n\n* **DETR** \n\n  * DETR is short for detection with transformer\n  * Paper accepted in 2020\n  * Uses a transformer layer after the feature extraction one\n  * Developed by FAIR\n  * To learn more, check the paperwithcodes [page](https://paperswithcode.com/method/detr)\n \n  <img src=\"https://paperswithcode.com/media/methods/Screen_Shot_2020-07-20_at_9.17.39_PM_ZHS2kmV.png\" width=480>\n\n\nThat was a lot of new concepts to groak, so as a reward, here is an approximate timeline: in red the one step models, and green the two steps ones. Notice that FPN doesn't have a category since it is used in both:\n\n\n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F172860%2F43b5252a12b471baa12e846bca60737d%2Fobject_detection_recent_timeline.png?generation=1600704962462342&alt=media\" width=720>\n\n\nThat's enough general architecture for now!\nIn the remaining parts, we will be focusing on the **EfficienDet** family of models, more specifically on the following Pytorch [implementation](https://github.com/google/automl/tree/master/efficientdet).","attachments":{"coco_object_detection_score.png":{"image/png":"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id=\"efficientdet\"></a>\n\n# EfficientDet Explained\n\nWhat is **EfficientDet** and how does it work?\n\n\nIn short, it is a recent (first submitted at the end of 2019, accepted in CVPR in 2020) very efficient (surprise surprise) object detection model.\n\nIn more details, it is a family of models designed by researchers from **Google brain**. The interesting thing is that some parts of it were designed using automatic **architecture search**, i.e. there was a meta-model that was trained to find the best hyper-parameters of the trained model automatically. Let's dive in more details.\n\n\n\nFirst, let's start with the model's **architecture**: \n\n<img src=\"https://camo.githubusercontent.com/0ebd0147a2340c5ef6c3e30f2e51ab0cc812e515/68747470733a2f2f73756e392d33352e757365726170692e636f6d2f633230353632382f763230353632383732362f64323962342f67546a705534676a327a632e6a7067\" width=480>\n\n\nAs you can see, there are **3 main** building blocks:\n\n1. a **classification** backbone block\n2. a **multi-scale features fusion** block\n3. a **class** and **bounding box** networks block\n\nIn more details, we have: \n\n* an **EfficientNet** (**Net** and not **Det**) backbone. This backbone was found using NAS (neural-architecture search) through the use of the MnasNet framework. More on this in the next section\n* **BiFPN** as a multi-scale fusion layer: once we have a classification network we need to efficiently extract features for the detection step. One extra challenge is to do so for multiple scales (learn more about this [here](https://d2l.ai/chapter_computer-vision/multiscale-object-detection.html)). These two challenges are solved efficiently using the BiFPN layer. Again, more on this in the next section.\n* **Two heads**: finally, everything is connected to two output networks. One for predicting the most likely label and one for predicting the detected bounding box (if any).\n\n\nTo experiment with the model and learn more, check this [colab notebook](https://github.com/google/automl/blob/master/efficientdet/tutorial.ipynb), the original [paper](https://arxiv.org/pdf/1911.09070.pdf), and the original [implementation](https://github.com/google/automl/tree/master/efficientdet). \n\n\nIn the following sections, we will explore each part in more details. Let's go!\n"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"effnet-backbone\"></a>\n## EfficientNet as a Backbone\n\nThis is the first part of the archtiecture. It uses the **EfficientNet** architecture and includes pre-trained weights.\n\nHere is a look at the overall archtitecture:\n\n\n\n<img src=\"https://miro.medium.com/max/1395/1*O1TZKZjafr9qqkxHxkJmAQ.png\" width=480>\n\nAs you can see, the interesting thing is that many elements of the model have been optimized using neural automatic search: **width**, **depth**, **number of channels**, and **resolution**.\n\nTo learn more about this **EfficientNet** backbone, read the original paper [here](https://arxiv.org/pdf/1905.11946.pdf), the blog [post](https://ai.googleblog.com/2019/05/efficientnet-improving-accuracy-and.html), and the implementation [here](https://github.com/google/automl/tree/master/efficientdet/backbone) (from the **efficientdet** repo)."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"bifpn\"></a>\n## BiFPN as a Multi-Scale Fusion Layer\n\nOnce we have a classification network, one important question to ask is: how to move from the **classification** model to an **object detection** one? This is cleverly solved by using features maps (i.e. intermediate learned representations). Another question is how to detect multiple objects having different sizes (for example a small cat and a car on the same image)? This is solved by taking features maps having different sizes. \n\nIn most modern object detection architectures, both problems are solved at once using an FPN layer. BiFPN, as its name indicates, builds upon the ideas of the FPN layer and adds one simple idea: instead of simply aggregating the different representations in a top-down fashion, it takes the PANet approach (i.e. top-down and bottom-up connections) and optimizes cross-scale connections.\n\nOne last trick is to use a weighted feature fusion instead of the unweighted FPN approach (the weights are learned as well) and normalize these weights using a fast normalization procedure (i.e. normalize by the sum instead of using softmax). Here is one example of a BiFPN computation from the paper:\n\n\n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F172860%2F612b65f04d5732669dbe04d5f0fc907d%2Fbifpn_computation_example.png?generation=1601114628541834&alt=media\" width=480>\n\n\nAll these tricks make the BiFPN layer both efficient and accurate. We will see one additional trick applied in the next and last section. Check the following graph to learn more about other FPN variations (including PANet and BiFPN):\n\n\n<img src=\"https://miro.medium.com/max/840/1*funGGmYqT6f2VkRnhqd2rA.png\" width=480>\n\n\n\nFinally, to learn more about FPN and BiFPN, check the papeswithcode [page](https://paperswithcode.com/method/bifpn), this [blog post](https://towardsdatascience.com/review-fpn-feature-pyramid-network-object-detection-262fc7482610), and this [one](https://medium.com/@jonathan_hui/understanding-feature-pyramid-networks-for-object-detection-fpn-45b227b9106c) as well. \n\nLet's move to the next step: the prediction networks."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"heads\"></a>\n\n## Two Heads\n\nThe third ingredient to the mix is the **two heads network**:\n\n- one for predicting the coordinates of the **bounding box**\n- one for predicting the **class** (the probability of each class to be more precise)\n\nEach of the two networks take as input all the ouptuts of the previous **BiFPN layer**. Then we have two fully-connected layers before getting the final values. As simple as that!\n\nWe close this section with the last trick: compound scaling."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"scalings\"></a>\n\n## Compound Scaling\n\n\nOne last ingredient to the mix is how the network is scaled. Indeed, this is a trick often used to improve the performance \nof networks. The most common way to do it is to scale the backbone's width and depth. \n\nIn the EfficientDet model, the EffincientNet backbone is scaled reusing the same values in the original network.\nThe interesting additional thing is the scaling of the BiFPN and prediction networks.\nIn fact, instead of using only one BiFPN and one prediction networks, these components are repeated. Finally, width ($W$), depth ($D$), and input resolution ($R$) in the different sections are scaled usign one single parammeter $\\phi$ in this fashion:\n\n\n\n- 1. $W_{bifpn} = 64 . (1.35^{\\phi})$ and $D_{bifpn} = 3 + \\phi$ for the **BiFPN** part\n- 2. $W_{pred} = W_{bifpn}$ and $D_{bifpn} = 3 + \\phi$ for the prediction part\n- 3. $R_{input} = 512 + \\phi . 128$ for the input image resolution. Notice that it should be divisible by 128 since we take features from levels 3 to 7 ($128 = 2 ^{7}$).\n\n\nHere is the table for the different **EfficientDet** variants: the bigger $\\phi$ is, the bigger the model:\n    \n<img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F172860%2F4b349ddd45bddd490ae3bc5079cc0e25%2Fefficientdet_scalings.png?generation=1601122425468830&alt=media\" width=480>\n\n\nTo finish this section, notice that the $1.35$ value in the first equation has been optimized using grid search (i.e. different values are tested and the one giving the best score is selected) over ${1.2, 1.25, 1.3, 1.35, 1.4, 1.45}$ values.\n\n\nThat's it for the model's architecture. Time to move to the application!"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"application\"></a>\n# Application to Global Wheat Challenge"},{"metadata":{},"cell_type":"markdown","source":"<img src=\"https://storage.googleapis.com/kaggle-media/competitions/UofS-Wheat/descriptionimage.png\">\n\n\nNow that the theory makes (hopefully) more sense, let's move to the application side of things.\nIn the above figure, you can see a patch of wheat heads.\n\nThat's the competition's banner and that's what we are predicting: finding the bounding boxes of wheat heads.\n\nAs stated in the introduction, we will be using the **EfficientDet** model introduced above. \n\nHere is a rough sketch of the plan:\n\n1. Understand the dataset, the task, and the evaluation metric\n2. Process the data so that it can be used with an efficientdet model\n3. Train the model \n4. Predict on test images"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"understanding\"></a>\n\n## Understanding the Task\n\nAs you have guessed it, the task of this competition is to predict the bounding boxes of wheat heads in different images.\nThe images have a varying number of wheat heads, colors, orientations, and so on making the task more challenging.\n\nTo further understand the task, let's explore the wheat images and the associated bounding boxes:  \n\n* Train images: \n\n    * There is a toal of **3422** unique train images. The code to get this number:\n    \n    ``` python \n    from pathlib import Path\n    train_paths = Path(\"/path/to/train\")\n    len(list(train_paths.glob(\"*\")))\n    ``` \n    \n    * There is a total of **3373** unique images with masks\n    * Thus some images don't have any masks\n    * There is a toal of **147793** masks\n    * Thus, on average, there are **43.8** masks per image\n    * The image with the most masks contains **116**. It is the image with id `35b935b6c`.\n    * All the train images have the same size: 1024 x 1024. \n    * There are 3 channels: R, G, B.\n    * The train images come from **7** different sources. Here is the distribution: \n\n    ``` python\n        {'arvalis_1': 1055,\n        'arvalis_2': 204,\n        'arvalis_3': 559,\n        'ethz_1': 747,\n        'inrae_1': 176,\n        'rres_1': 432,\n        'usask_1': 200}\n    ``` \n        \n    * **3** of these sources are probably similar: *arvalis_1*, *arvalis_2*, and *arvalis_3*. Most likely, the breakdown is by the competition sponsors/organisers?\n    * Bounding boxes where added using this [tool](https://github.com/jsbroks/coco-annotator).\n    * You can find resized datasets [here](https://www.kaggle.com/c/global-wheat-detection/discussion/160408).\n    * There are some data quality issues: masks [too big](https://www.kaggle.com/c/global-wheat-detection/discussion/159578), or [missing masks](https://www.kaggle.com/c/global-wheat-detection/discussion/163263). The organizers are working on a fix for the private test dataset (as far as I know).\n    * The average bounding box area is **6843**, the smallest is only **2**, and the largest is **529788**! Here attached the two images with the largest (upper right including many smaller) and the smallest (it is the in the lower right corner, at the edge) bounding boxes: \n    <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2F51306c59989506fbc085778805afaea0%2F42e6efaaa_with_bbox.png?generation=1594240530216553&amp;alt=media\" width=480>\n\n    <img src=https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2Fb4859bccc9fe7de7d7a19385479ab34f%2Fd0912a485_with_bbox.png?generation=1594240509985483&amp;alt=media width=480>\n\n    * The bbox area histogram with the top 1000 values truncated and the bottom 100 as well:\n    ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2F6397d02cd4ada74403ae0eaa955394ce%2Fhist_truncated.png?generation=1594242665230885&amp;alt=media)\n\n    * For more details about the dataset creation, check this [paper](https://arxiv.org/pdf/2005.02162.pdf). It contains a lot of statistics and data acquisition methodolgy descritption, so make sure to check it. Here are some graphs from the paper:  \n    <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2F063dea7e597defdd1b44fdd3bab843be%2Fwheat_dataset_table.png?generation=1593898190270563&amp;alt=media\" width=480>\n    <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2F518f78637d9026e7ee76380745749a93%2Foriginal_wheat_images.png?generation=1593898211077093&amp;alt=media\" width=480>\n    <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2F6dd629a68c99e0f840a8c446a8bc1092%2Fwheat_table_statistics.png?generation=1593898390536691&amp;alt=media\" width=480>\n\n\n\n* Test images:\n\n    * Only **10** images have been made public. The code to get this: \n    \n    ``` python \n        from pathlib import Path\n        test_paths = Path(\"/path/to/test\")\n        len(list(test_paths.glob(\"*\")))\n    ```\n    \n    * Don't worry though, there is a \"real\" test dataset that runs when you submit your inference kernel.\n    * The test dataset has been collected from different sources than the train. This is an important aspect of the competition for sure.\n    * There are few images in the test dataset that aren't 1024 x 1024. These will be fixed in the private part as far as I know.\n    * More insights about the test dataset could be found in [this](https://www.kaggle.com/c/global-wheat-detection/discussion/149770) discussion.  \n\n* Short code snippets: \n\n\n  * Load an image and overlay the corresponding mask(s): \n    \n    ``` python \n        from pathlib import Path\n\n        img_id = \"ID_OF_IMAGE\"\n        img_path = Path(f\"/path/to/train/{img_id}.jpg\")\n        img = Image.open(img_path)\n        draw = ImageDraw.Draw(img)\n        bboxes = train_labels_df.loc[lambda df: df[\"image_id\"] == img_id, \"bbox\"].tolist()\n        # The box contains the upper left corner (x, y) coordinates then width and height.\n        # So we need to change these to (x1, y1) and (x2, y2) where they are the upper \n        # left and lower right corners\n        for bbox in bboxes:\n            x, y, w, h = eval(bbox)\n            transformed_bbox = [x, y, x + w, y + h]\n            draw.rectangle(transformed_bbox, outline=\"black\", width=3)\n        img.save(\"/path/to/output/{img_id}.png\")\n        img\n    ```\n    \n    <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2Fe56c560fc347f24e44a9840c3afbf61c%2Fimag_with_bbox.png?generation=1593939578542921&amp;alt=media\" width=480>\n\n   * Extracting bounding boxes coordinates, width, height, and area: \n    \n    ``` python \n        import pandas as pd\n        train_labels_df = pd.read_csv(\"path/to/train/labels.csv\")\n\n        x = []\n        y = []\n        w = []\n        h = []\n        for bbox in train_labels_df['bbox']:\n            bbox = eval(bbox)\n            x.append(bbox[0])\n            y.append(bbox[1])\n            w.append(bbox[2])\n            h.append(bbox[3])\n\n        processed_train_labels_df = train_labels_df.copy()\n        processed_train_labels_df[\"x\"] = x\n        processed_train_labels_df[\"y\"] = y\n        processed_train_labels_df[\"w\"] = w\n        processed_train_labels_df[\"h\"] = h\n\n        processed_train_labels_df[\"area\"] = processed_train_labels_df[\"w\"] * processed_train_labels_df[\"h\"]\n        processed_train_labels_df[\"x2\"] = processed_train_labels_df[\"x\"] + processed_train_labels_df[\"w\"]\n        processed_train_labels_df[\"y2\"] = processed_train_labels_df[\"y\"] + processed_train_labels_df[\"h\"]\n    ```\n\n\n* Metric\n\n    * There are many components to this metric: first, we compute Jaccard/[IoU](https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for-object-detection/) scores, then for some threshold `t`, the wheat head is a TP if the IoU is above it, finally we compute the [precision](https://en.wikipedia.org/wiki/Precision_and_recall) for this threshold. Then, average over the thresholds (given the AP) and over images (given mAP, mean average prediction).\n    * Thus, there are two levels of averaging: over the thresholds and then over the images. \n    * Notice that there are some edge-cases where the precision will be 0: no mask is predicted and there is at least one, a mask is predicted but there aren't any.\n\n* Some backbone models that work well for object detection: \n\n    * [YOLOv5](https://github.com/ultralytics/yolov5)\n    * [Detectron2](https://github.com/facebookresearch/detectron2): this isn't a single model but rather a collection of object detection models. It contains Faster R-CNN, RetinaNet and many more. \n\n* Previous similar competitions:\n\n    * [TGS Salt Identification](https://www.kaggle.com/c/tgs-salt-identification-challenge/overview). This is an object detection competition with exactly the same metric. Here is a link to the [first place](https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/69291) solution, the code [repo](https://github.com/ybabakhin/kaggle_salt_bes_phalanx), and a [paper](https://arxiv.org/pdf/1904.04445.pdf) published.\n    * [Severstal: Steel Defect Detection](https://www.kaggle.com/c/severstal-steel-defect-detection/). This isn't exactly an object detection competition but rather an **semantic segmentation** one. Here is a link the [first place](https://www.kaggle.com/c/severstal-steel-defect-detection/discussion/114254) solution. \n    * [Airbus Ship Detection](https://www.kaggle.com/c/airbus-ship-detection). Another instance segmentation competition. Here is the 4th place solution. The metric here is close to the current competition but instead of AP, it uses [F2](https://www.quora.com/What-is-the-F2-score-in-machine-learning) score. \n    * [Data Science Bowl 2018](https://www.kaggle.com/c/data-science-bowl-2018/overview/evaluation). Yet another semantic segmentation competition. The evaluation metric is exactly the same. Here is the [top solution](https://www.kaggle.com/c/data-science-bowl-2018/discussion/54741). \n    \n* Some interesting ideas:\n\n    * Multi-rounds pseudo-labelling (graph below from [here](https://arxiv.org/pdf/1904.04445.pdf))\n    * Train a classifier first to find images without wheat heads\n    * Randomly cropping the train images\n    * Using augmentation. [Albumentations](https://github.com/albumentations-team/albumentations) is a great library for that.\n    * Use BCE (binary cross entropy) + Jaccard as a loss (given some weight to each) or [Lovasz](https://arxiv.org/pdf/1705.08790.pdf)\n    * Train using one loss for some epochs then use another one\n    * Average over the last n snapshots for more generalization\n    \n        <img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F172860%2Fb8105b2f464ab58a47bf068debbe24c9%2Fkround_pseudo_labeling.png?generation=1593898259088583&amp;alt=media\" width=480>\n    \n    "},{"metadata":{},"cell_type":"markdown","source":"<a id=\"evaluation\"></a>\n\n## Evaluation Metric"},{"metadata":{},"cell_type":"markdown","source":"The evaluation metric for object detection is quite tricky (when compared to object classification).\nHere is how it is computed:\n\n1. Predict the bounding box for each wheat head and give a confidence score\n2. Compute the intersection over union of each bounding box \n3. Re-order the predictions from highest score to lowest\n4. Now we can compute the recall and precision for the ranked bounding boxes\n5. From there, we can compute the average precision: this is the sum over 11 break points of the precision vs recall curve.\n6. Since we have only one class, this is also the mAP.\n\n\nIf this explanation isn't clear enough, check the following [paper](https://raw.githubusercontent.com/rafaelpadilla/Object-Detection-Metrics/master/paper_survey_on_performance_metrics_for_object_detection_algorithms.pdf) detailing object detection metrics and how they are computed."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"model\"></a>\n\n## The Model"},{"metadata":{},"cell_type":"markdown","source":"Enough with theory, let's move to the implementation!\n\nSimilarly the the previous NLP notebook, I will be using [Pytorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning) to implement the model. \nFor that, we will start by defining the model part then move to the data processing, evaluation, and prediction.\n\nLet's get started!"},{"metadata":{},"cell_type":"markdown","source":"To make things easier (DRY principle), I will be using the following **EfficientDet** [model](https://github.com/rwightman/efficientdet-pytorch).\n\n\nTo create the model, the code snippet is quite simple (D5 **EfficientDet** here but you can use the one that suits your needs): \n\n\n``` python\n\nfrom effdet import get_efficientdet_config, EfficientDet, DetBenchTrain\nfrom effdet.efficientdet import HeadNet\n\n\n\ndef get_train_efficientdet():\n    # Get the model's config\n    config = get_efficientdet_config(\"tf_efficientdet_d5\")\n    # Create the model\n    net = EfficientDet(config, pretrained_backbone=False)\n    # Load pretrained EfficientDet weights\n    checkpoint = torch.load(\"path/to/weights\")\n    net.load_state_dict(checkpoint)\n    # Change the number of classes to 1 (only predicting wheat)\n    config.num_classes = 1\n    config.image_size = 256\n    # Add the head with the updated parameters\n    head = HeadNet(\n        config,\n        num_outputs=config.num_classes,\n        norm_kwargs=dict(eps=0.001, momentum=0.01),\n    )\n    # Attach the head\n    net.class_net = head\n    return DetBenchTrain(net, config)\n\n```"},{"metadata":{},"cell_type":"markdown","source":"Notice that for the most recent version of the `effdet` library, you can use the create_model and/or the create_mode_from_config functions for a cleaner code.\n\n\nHere is a sample code: \n\n\n```\nfrom effdet import create_model\nnet = create_model('tf_efficientdet_d5', bench_task='train', num_classes=1, bench_labeler=True)\n```"},{"metadata":{},"cell_type":"markdown","source":"In what follows, we will use this code snippet to create the model. Next, let's see how we can \ncreate a `WheatDataset`: if you aren't familiar with Pytorch's `Dataset` concept, check it [here](https://pytorch.org/docs/stable/data.html#torch.utils.data.Dataset). "},{"metadata":{},"cell_type":"markdown","source":"<a id=\"dataset\"></a>\n## The Dataset"},{"metadata":{},"cell_type":"markdown","source":"Before I start, notice that some of the code (mostly?) is inspired from this [notebook]( https://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train), so go check it out and thank [Peter](https://www.kaggle.com/pestipeti) for making it!"},{"metadata":{"trusted":true},"cell_type":"code","source":"from torch.utils.data import DataLoader, Dataset\nimport torch\nfrom PIL import Image\nimport albumentations as A\nfrom albumentations.pytorch.transforms import ToTensorV2\nimport numpy as np\nimport pandas as pd\nfrom pathlib import Path\n\n# Using a small image size so it trains faster but do try bigger images \n# for better performance.\nIMG_SIZE = 256\n\ndef get_train_transforms():\n    return A.Compose(\n        [\n            A.RandomSizedCrop(min_max_height=(800, 800), height=IMG_SIZE, width=IMG_SIZE, p=0.5),\n            A.OneOf([\n                A.HueSaturationValue(hue_shift_limit=0.2, sat_shift_limit= 0.2, \n                                     val_shift_limit=0.2, p=0.9),\n                A.RandomBrightnessContrast(brightness_limit=0.2, \n                                           contrast_limit=0.2, p=0.9),\n            ],p=0.9),\n            A.ToGray(p=0.01),\n            A.HorizontalFlip(p=0.5),\n            A.VerticalFlip(p=0.5),\n            A.Resize(height=256, width=256, p=1),\n            A.Cutout(num_holes=8, max_h_size=64, max_w_size=64, fill_value=0, p=0.5),\n            ToTensorV2(p=1.0),\n        ], \n        p=1.0, \n        bbox_params=A.BboxParams(\n            format='pascal_voc',\n            min_area=0, \n            min_visibility=0,\n            label_fields=['labels']\n        )\n    )\n\ndef get_valid_transforms():\n    return A.Compose(\n        [\n            A.Resize(height=IMG_SIZE, width=IMG_SIZE, p=1.0),\n            ToTensorV2(p=1.0),\n        ], \n        p=1.0, \n        bbox_params=A.BboxParams(\n            format='pascal_voc',\n            min_area=0, \n            min_visibility=0,\n            label_fields=['labels']\n        )\n    )\n\n\n\ndef get_test_transforms():\n    return A.Compose([\n            A.Resize(height=IMG_SIZE, width=IMG_SIZE, p=1.0),\n            ToTensorV2(p=1.0),\n        ], p=1.0)\n\n\n\n\nclass WheatDataset(Dataset):\n\n    def __init__(self, df = None, mode = \"train\", image_dir = \"\", transforms=None):\n        super().__init__()\n        if df is not None:\n            self.df = df.copy()\n            self.image_ids = df['image_id'].unique()\n        else:\n            # Test case\n            self.df = None\n            self.image_ids = [p.stem for p in Path(image_dir).glob(\"*.jpg\")]\n        self.image_dir = image_dir\n        self.transforms = transforms\n        self.mode = mode\n\n    def __getitem__(self, index: int):\n\n        image_id = self.image_ids[index]\n        # Could be one or many rows.\n\n        image = Image.open(f'{self.image_dir}/{image_id}.jpg').convert(\"RGB\")\n        # Convert to Numpy array\n        image = np.array(image)\n        image = image / 255.0\n        image = image.astype(np.float32)\n\n\n        if self.mode != \"test\":\n    \n            records = self.df[self.df['image_id'] == image_id]\n\n            area = records[\"area\"].values\n            area = torch.as_tensor(area, dtype=torch.float32)\n\n            boxes = records[[\"x\", \"y\", \"x2\", \"y2\"]].values\n\n            # there is only one class, so always 1.\n            labels = torch.ones((records.shape[0],), dtype=torch.int64)\n            \n            # suppose all instances are not crowd.\n            iscrowd = torch.zeros((records.shape[0],), dtype=torch.int64)\n        \n            target = {}\n            target['boxes'] = boxes\n            target['labels'] = labels\n            # target['masks'] = None\n            target['image_id'] = torch.tensor([index])\n            target['area'] = area\n            target['iscrowd'] = iscrowd\n            # These are needed as well by the efficientdet model.\n            target['img_size'] = torch.tensor([(IMG_SIZE, IMG_SIZE)])\n            target['img_scale'] = torch.tensor([1.])\n        \n        else:\n\n            # test dataset must have some values so that transforms work.\n            target = {'cls': torch.as_tensor([[0]], dtype=torch.float32),\n                      'bbox': torch.as_tensor([[0, 0, 0, 0]], dtype=torch.float32),\n                      'img_size': torch.tensor([(IMG_SIZE, IMG_SIZE)]),\n                      'img_scale': torch.tensor([1.])}\n\n\n        if self.mode != \"test\":\n            if self.transforms:\n                sample = {\n                    'image': image,\n                    'bboxes': target['boxes'],\n                    'labels': labels\n                }\n                if len(sample['bboxes']) > 0:\n                    # Apply some augmentation on the fly. \n                    sample = self.transforms(**sample)\n                    image = sample['image']\n                    boxes = sample['bboxes']\n                    # Need yxyx format for EfficientDet.\n                    target['boxes'] = torch.stack(tuple(map(torch.tensor, zip(*boxes)))).permute(1, 0)\n\n        else:\n            sample = {\n                'image': image,\n                'bbox': target['bbox'],\n                'cls': target['cls']\n            }\n            image = self.transforms(**sample)['image']\n\n        return image, target\n\n    def __len__(self) -> int:\n        return len(self.image_ids)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"So, what have we done above?\n\n1. Defined some transforms using the [albumentations](https://albumentations.ai/) library for the three phases: train, validation, and test.\n2. Setup the `WheatDataset`. Notice there are some data wrangling to get the correct format while using the `EfficientDet` implementation.\n\nLet's check that this implementation works by sampling from the `WheatDataset`. \nBefore that one small detour to process the labels' DataFrame and add some useful metadata such as the bounding box `area` and\nthe lower corner's coordiantes."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Some processing to add some metadata to the labels DataFrame\ntrain_labels_df = pd.read_csv(\"../input/global-wheat-detection/train.csv\")\n\ntrain_labels_df['bbox'] = train_labels_df['bbox'].apply(eval)\n\nx = []\ny = []\nw = []\nh = []\nfor bbox in train_labels_df['bbox']:\n    x.append(bbox[0])\n    y.append(bbox[1])\n    w.append(bbox[2])\n    h.append(bbox[3])\n    \nprocessed_train_labels_df = train_labels_df.copy()\nprocessed_train_labels_df[\"x\"] = x\nprocessed_train_labels_df[\"y\"] = y\nprocessed_train_labels_df[\"w\"] = w\nprocessed_train_labels_df[\"h\"] = h\n\n\nprocessed_train_labels_df[\"area\"] = processed_train_labels_df[\"w\"] * processed_train_labels_df[\"h\"]\nprocessed_train_labels_df[\"x2\"] = processed_train_labels_df[\"x\"] + processed_train_labels_df[\"w\"]\nprocessed_train_labels_df[\"y2\"] = processed_train_labels_df[\"y\"] + processed_train_labels_df[\"h\"]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Create stratified folds, here using the source.\n# This isn't the most optimal way to do it but I will leave it to you \n# to find a better one. ;)\nfrom sklearn.model_selection import StratifiedKFold\nskf = StratifiedKFold(n_splits=5)\nfor fold, (train_index, valid_index) in enumerate(skf.split(processed_train_labels_df, \n                                                            y=processed_train_labels_df[\"source\"])):\n    processed_train_labels_df.loc[valid_index, \"fold\"] = fold","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"processed_train_labels_df.sample(2).T","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# We need to set a folder to get images\nTRAIN_IMG_FOLDER = \"../input/global-wheat-detection/train\"\n\n# This is the transforms for the training phase\ntrain_transforms = get_train_transforms()\n\n\n\n\ntrain_dataset = WheatDataset(\n    \n    processed_train_labels_df, mode=\"train\", image_dir=TRAIN_IMG_FOLDER, transforms=train_transforms\n)\n\nimage, target = train_dataset[0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(image)\nprint(target)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pylab as plt\nfrom PIL import Image, ImageDraw\nimport pandas as pd\nfrom pathlib import Path\n\n\ndef plot_image_with_bboxes(img_id, df):\n    img_path = Path(TRAIN_IMG_FOLDER + f\"/{img_id}.jpg\")\n    img = Image.open(img_path)\n    draw = ImageDraw.Draw(img)\n    bboxes = df.loc[lambda df: df[\"image_id\"] == img_id, \"bbox\"]\n    # The box contains the upper left corner (x, y) coordinates then width and height.\n    # So we need to change these to (x1, y1) and (x2, y2) where they are the upper \n    # left and lower right corners\n    for bbox in bboxes:\n        x, y, w, h = bbox\n        transformed_bbox = [x, y, x + w, y + h]\n        draw.rectangle(transformed_bbox, outline=\"red\", width=3)\n    return img\n\n\n\nplot_image_with_bboxes(\"00333207f\", processed_train_labels_df)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Looks fine, awesome! Time to move to the training pipeline."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"pipeline\"></a>\n## Pytorch Lightning Complete Pipeline"},{"metadata":{},"cell_type":"markdown","source":"Alright, time to build a model. For that, we will be using the belvoed **Pytorch Lightning**. \nAs usual, we will start with the **model building block** then add the **processing** steps. As a first step, we install the **Pytorch Lightning** library using pip: `pip install pytorch_lightning`. \n\nNext, we install the [efficientdet](https://github.com/rwightman/efficientdet-pytorch) library, again using pip: `pip install effdet`. Notice that the **efficientdet** library needs **timm** (PyTorch Image Models library). For that, we also need to run: \n`pip install timm`. There is finally **omegaconf** and **pycocotools** (same using pip)."},{"metadata":{"trusted":true},"cell_type":"code","source":"!pip install --upgrade pip\n!pip install pytorch_lightning\n!pip install effdet --upgrade\n!pip install timm\n!pip install omegaconf\n!pip install pycocotools","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Everything is set, time to create the **EfficientDet** model using the code snippet presented above: the new `create_model` code snippet instead of the `get_train_efficientdet` function since we are using the latest `effdet` version. "},{"metadata":{"trusted":true},"cell_type":"code","source":"import torch\nfrom effdet import get_efficientdet_config, EfficientDet, DetBenchTrain\nfrom effdet.efficientdet import HeadNet\n\n\n# No longer works. :) \ndef get_train_efficientdet():\n    config = get_efficientdet_config('tf_efficientdet_d5')\n    net = EfficientDet(config, pretrained_backbone=False)\n    checkpoint = torch.load('../input/efficientdet/efficientdet_d5-ef44aea8.pth')\n    net.load_state_dict(checkpoint)\n    config.num_classes = 1\n    config.image_size = IMG_SIZE\n    net.class_net = HeadNet(config, num_outputs=config.num_classes, norm_kwargs=dict(eps=.001, momentum=.01))\n    return DetBenchTrain(net, config)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# New way that works!\n\nfrom effdet import create_model\n\n\ndef get_train_efficientdet():\n    # checkpoint_path='../input/efficientdet/efficientdet_d5-ef44aea8.pth'\n    return create_model('tf_efficientdet_d5', bench_task='train', num_classes=2, bench_labeler=True)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from pytorch_lightning import LightningModule\n\nclass WheatModel(LightningModule):\n    \n    \n    def __init__(self, df, fold):\n        super().__init__()\n        self.df = df\n        self.train_df = self.df.loc[lambda df: df[\"fold\"] != fold]\n        self.valid_df = self.df.loc[lambda df: df[\"fold\"] == fold]\n        self.image_dir = TRAIN_IMG_FOLDER\n        self.model = get_train_efficientdet()\n        self.num_workers = 4\n        self.batch_size = 8\n    \n    \n    def forward(self, image, target):\n        return self.model(image, target)\n    \n\n# Create a model for one fold.\nmodel = WheatModel(processed_train_labels_df, fold=0)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"model","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler\n\ndef collate_fn(batch):\n    return tuple(zip(*batch))\n\n# Let's add the train and validation data loaders.\n\ndef train_dataloader(self):\n    train_transforms = get_train_transforms()\n    train_dataset = WheatDataset(\n        self.train_df, image_dir=self.image_dir, transforms=train_transforms\n    )\n    return DataLoader(\n        train_dataset,\n        batch_size=self.batch_size,\n        sampler=RandomSampler(train_dataset),\n        pin_memory=False,\n        drop_last=True,\n        collate_fn=collate_fn,\n        num_workers=self.num_workers,\n    )\n\ndef val_dataloader(self):\n    valid_transforms = get_train_transforms()\n    valid_dataset = WheatDataset(\n        self.valid_df, image_dir=self.image_dir, transforms=valid_transforms\n    )\n    valid_dataloader = DataLoader(\n        valid_dataset,\n        batch_size=self.batch_size,\n        sampler=SequentialSampler(valid_dataset),\n        pin_memory=False,\n        shuffle=False,\n        collate_fn=collate_fn,\n        num_workers=self.num_workers,\n    )\n    iou_types = [\"bbox\"]\n    # Had to comment these since the evaluation doesn't work yet.\n    # More on this in the next section.\n    # coco = convert_to_coco_api(valid_dataset)\n    # self.coco_evaluator = CocoEvaluator(coco, iou_types)\n    return valid_dataloader\n\n\n\nWheatModel.train_dataloader = train_dataloader\nWheatModel.val_dataloader = val_dataloader","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\n# TODO: What should be changed in order to make it work?\ndef training_step(self, batch, batch_idx):\n    images, targets = batch\n    targets = [{k: v for k, v in t.items()} for t in targets]\n    # separate losses\n    images = torch.stack(images).float()\n    targets2 = {}\n    targets2[\"bbox\"] = [\n        target[\"boxes\"].float() for target in targets\n    ]  # variable number of instances, so the entire structure can be forced to tensor\n    targets2[\"cls\"] = [target[\"labels\"].float() for target in targets]\n    \"\"\"\n    targets2[\"image_id\"] = torch.tensor(\n        [target[\"image_id\"] for target in targets]\n    ).float()\n    targets2[\"img_scale\"] = torch.tensor(\n        [target[\"img_scale\"] for target in targets], device=\"cuda\"\n    ).float()\n    targets2[\"img_size\"] = torch.tensor(\n        [(IMG_SIZE, IMG_SIZE) for target in targets], device=\"cuda\"\n    ).float()\n    \"\"\"\n    losses_dict = self.model(images, targets2)\n\n    return {\"loss\": losses_dict[\"loss\"], \"log\": losses_dict}\n\ndef validation_step(self, batch, batch_idx):\n    images, targets = batch\n    targets = [{k: v for k, v in t.items()} for t in targets]\n    # separate losses\n    images = torch.stack(images).float()\n    targets2 = {}\n    targets2[\"bbox\"] = [\n        target[\"boxes\"].float() for target in targets\n    ]  # variable number of instances, so the entire structure can be forced to tensor\n    targets2[\"cls\"] = [target[\"labels\"].float() for target in targets]\n    \"\"\"\n    targets2[\"image_id\"] = torch.tensor(\n        [target[\"image_id\"] for target in targets]\n    ).float()\n    targets2[\"img_scale\"] = torch.tensor(\n        [target[\"img_scale\"] for target in targets], device=\"cuda\"\n    ).float()\n    targets2[\"img_size\"] = torch.tensor(\n        [(IMG_SIZE, IMG_SIZE) for target in targets], device=\"cuda\"\n    ).float()\n    \"\"\"\n    losses_dict = self.model(images, targets2)\n    loss_val = losses_dict[\"loss\"]\n    detections = losses_dict[\"detections\"]\n    # Back to xyxy format.\n    detections[:, :, [1,0,3,2]] = detections[:, :, [0,1,2,3]]\n    # xywh to xyxy => not necessary.\n    # detections[:, :, 2] += detections[:, :, 0]\n    # detections[:, :, 3] += detections[:, :, 1]\n\n    res = {target[\"image_id\"].item(): {\n                'boxes': output[:, 0:4],\n                'scores': output[:, 4],\n                'labels': output[:, 5]}\n            for target, output in zip(targets, detections)}\n    # iou = self._calculate_iou(targets, res, IMG_SIZE)\n    # iou = torch.as_tensor(iou)\n    # self.coco_evaluator.update(res)\n    return {\"loss\": loss_val, \"log\": losses_dict}\n\ndef validation_epoch_end(self, outputs):\n    # self.coco_evaluator.accumulate()\n    # self.coco_evaluator.summarize()\n    # coco main metric\n    # metric = self.coco_evaluator.coco_eval[\"bbox\"].stats[0]\n    # metric = torch.as_tensor(metric)\n    # tensorboard_logs = {\"main_score\": metric}\n    # return {\n    #     \"val_loss\": metric,\n    #     \"log\": tensorboard_logs,\n    #     \"progress_bar\": tensorboard_logs,\n    # }\n    pass\n\ndef configure_optimizers(self):\n    return torch.optim.AdamW(self.model.parameters(), lr=1e-4)\n\n\n\nWheatModel.training_step = training_step\n# Had to comment these since the evaluation doesn't work yet. More on this \n# in the next section.\n# WheatModel.validation_step = validation_step\n# WheatModel.validation_epoch_end = validation_epoch_end\nWheatModel.configure_optimizers = configure_optimizers\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"That's it, our `WheatModel` is ready now. Let's train it. For that, we will create a `Trainer` and set it \nto `fast_dev_run=True` for a quicker demo. Also, since it is in this mode, the `Trainer`\ndoesn't automatically save the weights at the end (correct me if I am wrong of course) so we\nneed to add a `torch.save` call at the end."},{"metadata":{"trusted":true},"cell_type":"code","source":"from pytorch_lightning import Trainer, seed_everything, loggers\n\nseed_everything(314)\n# Create a model for one fold.\n# As an exercise, try doing it for the other folds and chaning the Trainer. ;)\nmodel = WheatModel(processed_train_labels_df, fold=0)\nlogger = loggers.TensorBoardLogger(\"logs\", name=\"effdet-b5\", version=\"fold_0\")  \ntrainer = Trainer(gpus=1, logger=logger, fast_dev_run=True)\ntrainer.fit(model)\ntorch.save(model.model.state_dict(), \"wheatdet.pth\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"evaluation\"></a>\n\n# Evaluation "},{"metadata":{},"cell_type":"markdown","source":"Believe it or not, this is a part where I struggled the most. This isn't because of the tool but it was due to the \ncode that I was using. Indeed, the evaluation part is tied to the `torchvision` repo and I haven't found a simple way to import it.\nThus I needed to copy a lot of code as was done in artgor's notebook. I won't show this part since it is tedious and not very elegant. If you have found a better method, please share it with me in the comments section.\n\nAnother route I have tried is a similar one used [here](https://colab.research.google.com/github/pytorch/vision/blob/temp-tutorial/tutorials/torchvision_finetuning_instance_segmentation.ipynb#scrollTo=DBIoe_tHTQgV) where they have cloned the torchvision part from the Pytorch's repo then copying the necessary parts using cp (instead of manually doing it). I am sure it works eventually but I won't do this here since the notebook is long enough already and I am being a little lazy. I will try to make this section work later on. "},{"metadata":{"trusted":true},"cell_type":"code","source":"# Download TorchVision repo to use some files from\n# references/detection\n\"\"\"\n!git clone https://github.com/pytorch/vision.git\n!cd vision\n!git checkout v0.3.0\n\n!cp references/detection/utils.py ../\n!cp references/detection/transforms.py ../\n!cp references/detection/coco_eval.py ../\n!cp references/detection/engine.py ../\n!cp references/detection/coco_utils.py ../\n\"\"\"","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"To finish this section, let's make some predictions."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"inference\"></a>\n\n## Inference"},{"metadata":{},"cell_type":"markdown","source":"Mostly inspired (i.e. copied ;)) from [here](https://www.kaggle.com/shonenkov/inference-efficientdet). Again, thanks \n**Alex Shonenkov**. I won't go over the formatting step to make a proper submission file. \nCheck the notebook if you want to learn about these final steps.\n\nAlso, in a better world, I would have made this part using Pytorch Lightning but I am little overwhelmed with \nthis very lengthy notebook so it is enough for now. ;)"},{"metadata":{"trusted":true},"cell_type":"code","source":"from effdet import DetBenchPredict\n\n\ndef get_test_efficientdet(checkpoint_path):\n    config = get_efficientdet_config('tf_efficientdet_d5')\n    net = EfficientDet(config, pretrained_backbone=False)\n\n    config.num_classes = 1\n    config.image_size=IMG_SIZE\n    net.class_net = HeadNet(config, num_outputs=config.num_classes, \n                            norm_kwargs=dict(eps=.001, momentum=.01))\n\n    checkpoint = torch.load(checkpoint_path)\n    net.load_state_dict(checkpoint, strict=False)\n    net = DetBenchPredict(net, config)\n    return net\n\n\n\ndef make_predictions(model, images, score_threshold=0.22):\n    images = torch.stack(images).float()\n    predictions = []\n    targets = torch.tensor([1]*images.shape[0])\n    img_scales = torch.tensor(\n        [1 for target in targets]\n    ).float()\n    img_sizes = torch.tensor(\n        [(IMG_SIZE, IMG_SIZE) for target in targets]\n    ).float()\n    with torch.no_grad():\n        detections = model(images, img_scales, img_sizes)\n        for i in range(images.shape[0]):\n            pred = detections[i].detach().cpu().numpy()\n            boxes = pred[:,:4]    \n            scores = pred[:,4]\n            indexes = np.where(scores > score_threshold)[0]\n            boxes = boxes[indexes]\n            boxes[:, 2] = boxes[:, 2] + boxes[:, 0]\n            boxes[:, 3] = boxes[:, 3] + boxes[:, 1]\n            predictions.append({\n                'boxes': boxes[indexes],\n                'scores': scores[indexes],\n            })\n    return predictions","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"TEST_IMG_FOLDER = \"../input/global-wheat-detection/test\"\n\n\ntest_model = get_test_efficientdet(\"wheatdet.pth\")\n\ntest_dataset = WheatDataset(\n    \n    None, mode=\"test\", image_dir=TEST_IMG_FOLDER, transforms=get_test_transforms()\n)\n\nimage, _ = test_dataset[0]\n\npredictions = make_predictions(test_model, [image])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"predictions","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Hurray, we have predictions!"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"advanced\"></a>\n\n# Advanced Concepts\n\n\nBefore finishing this (lengthy) notebook, I wanted to talk about few **advanced concepts** to get better results\nparticularly for object detection but they do work for many computer vision tasks. \nAs you might have seen, the results you get from training the model presented above are quite good but not \nenough to be competitive. Indeed, winning solutions used EfficientDet augmented with few more tricks. \n\nHere are some advanced concepts to get you better results: \n\n- Mosaic augmentation\n- TTA \n- WBF blending\n\nLet's start with **mosaic augmentation**."},{"metadata":{},"cell_type":"markdown","source":"<a id=\"augmentation\"></a>\n\n## Mosaic Augmentation"},{"metadata":{},"cell_type":"markdown","source":"This technique consists in stitching together different images to form a bigger one. \nThe more diverse the images, the better it is. \nIf you are curious, you can check an example of how to use it\n[here](https://www.kaggle.com/c/global-wheat-detection/discussion/172418) from the winning competition solution. The following example is extracted from the same post, thanks again to [DungNB](https://www.kaggle.com/nguyenbadung) for the write-up!\n\n![custom_mosaic_augmentation.png](attachment:custom_mosaic_augmentation.png)\n\n\nHere is a simple explanation using cat images: \n\n\n\n![mosaic_augmentation_resized.png](attachment:mosaic_augmentation_resized.png)","attachments":{"custom_mosaic_augmentation.png":{"image/png":"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"},"mosaic_augmentation_resized.png":{"image/png":"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"}}},{"metadata":{},"cell_type":"markdown","source":"<a id=\"tta\"></a>\n\n## TTA\n\n\nTTA, short for **test-time augmentation**, is a popular technique for getting better performance for computer vision tasks and you will often encounter it when doing Kaggle computer vision competitions.\n\nHow does it work?\n\nThe basic idea is quite simple: \n\n1. Create additional test images from the provided ones using **augmentation** techniques.\n2. Predict using the trained model: you will have the prediction for the original image plus the augmented ones.\n3. Blend the predictions: more on this in the next section \n\nFor the augmentation step, horizantal and vertical flips are quite common strategies for TTA. Notice that since this step happens during inference time and since code competitions have time limits, you can't use a lot of augmentation. \n2 or 3 additional images per original test one is more than enough.\nFinally, for object detection, since there is a bounding box to predict, the augmentation step should preserve the shape of the bounding box. Thus some augmentations aren't allowed (for instance 90 degrees rotations). \n\nTo finish this section, here is an illustration (again, using cats :p)\n\n\n![tta_resized.png](attachment:tta_resized.png)","attachments":{"tta_resized.png":{"image/png":"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"}}},{"metadata":{},"cell_type":"markdown","source":"<a id=\"wbf\"></a>\n\n## WBF Blending\n\n\nIf you are accustomed to **object detection** tasks and challenges, you may have heard about **NMS** (short for non-maximum suppresion). Here is a short description of its pseudo-code:\n\n<img src=\"https://miro.medium.com/max/840/1*CuqLjro26cHShpQVO1rgdQ.png\" width=480>\n\n\n\n\n\nCheck this [post](https://towardsdatascience.com/non-maximum-suppression-nms-93ce178e177c) for more details (the figure above is from it).\n\n\nThis technique is used to merge many boxes (called proposals) from one model and can be used to merge the results of many models as well. \n\nHere, we will go over another technique called **weighted-boxes fusion** or (**WBF** in short). \n\nTo get started, you can check the Github implementation [here](https://github.com/ZFTurbo/Weighted-Boxes-Fusion), the [paper](https://arxiv.org/pdf/1910.13302.pdf) or this great [notebook](https://www.kaggle.com/shonenkov/wbf-approach-for-ensemble) again from [Alex Shonenkov](https://www.kaggle.com/shonenkov), so thanks!\n\nSo how does it work and how is it different? Let's have a look at the following schema (from the **WBF** paper)\n\n\n![wbf_schema.png](attachment:wbf_schema.png)\n\n\nIf you may have noticed, the **WBF** algorithm \"made\" a bounding box that isn't any of the proposed ones whereas NMS came up with one from the proposals. Indeed, that's one of the big differences between the two: how different proposals are merged. For the WBF case, the main objective is to compute a new confidence score C from existing confidence scores and then use it to compute the blended bounding box coordinates and confidence as a weighted mean (or other functions).\n\n\nFinally, if you want even more blending techniques, you can explore these techniques:\n\n- Soft-NMS: similar to NMS (non-maximum suppression) but with a soft selection criterion\n\n<img src=\"https://miro.medium.com/max/794/1*G6-phMqZbwgozsFwe5FDUw.png\" width=480>\n\n\n- Non-maximum weighted (NMW): this is the same as the NMS but computing a weighted a bounding box instead\nof computing only one.\n\n\n\n\n\n","attachments":{"wbf_schema.png":{"image/png":"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"}}},{"metadata":{},"cell_type":"markdown","source":"<a id=\"wrap-up\"></a>\n\n# To Wrap Up"},{"metadata":{},"cell_type":"markdown","source":"That's it for today. If you made it this far, congratulations!\n\nBy now, you should have acquired basic knowledge of **object detection** and **computer vision** more generally, you can \nnow go and build models. Congratulations on gaining a new (super) power!\n\nStay tuned for the next notebook and in the meantime, happy kaggling!"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"go-beyond\"></a>\n## To Go Beyond"},{"metadata":{},"cell_type":"markdown","source":"Going further, check these resources to expand your understanding: \n    \n- Pytorch's torchvision object detection tutorialn very: https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html\n- Learn more about efficientdet here: https://blog.roboflow.ai/breaking-down-efficientdet/\n- If you want to learn more about computer vision using deep learning: A great playlist if you like videos: https://www.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r\n- More specifically, this video is great for object detection: https://www.youtube.com/watch?v=TB-fdISzpHQ&list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r&index=16&t=0s\n\n- A good explanation of the differences between evaluation metrics: https://stats.stackexchange.com/questions/238684/what-are-the-difference-between-dice-jaccard-and-overlap-coefficients\n\n- A complete explanation of EfficientDet: https://towardsdatascience.com/googles-efficientdet-an-overview-8d010fa15860\n- Another EfficientDet Medium post: https://medium.com/@nainaakash012/efficientdet-scalable-and-efficient-object-detection-ea05ccd28427\n- A paper comparing human-level performance vs some deep learning algorithms on vision tasks: https://arxiv.org/pdf/1706.06969.pdf\n- Some augmentations notebook: https://www.kaggle.com/nvnnghia/awesome-augmentation\n- Another EfficientDet Pytorch implementation: https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch\n- A very thorough series of object detection medium posts: https://medium.com/@jonathan_hui/object-detection-series-24d03a12f904"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}