{ "total": 547, "topics": [ { "id": 173586, "title": "Leaderboard Update Is Underway", "comment_count": 159, "views": 0, "votes": 30, "reused": true }, { "id": 168693, "title": "Submission to ECCV 2020 / CVPPP 2020", "comment_count": 7, "views": 0, "votes": 8, "reused": true }, { "id": 172589, "title": "Thank you & reminder for paper submissions", "comment_count": 28, "views": 0, "votes": 8, "reused": true }, { "id": 148562, "title": "New to Machine Learning or to Kaggle? ", "comment_count": 37, "views": 0, "votes": 5, "reused": true }, { "id": 167298, "title": "Submission Compliance", "comment_count": 16, "views": 0, "votes": 31, "reused": true }, { "id": 148561, "title": "External Data Thread", "comment_count": 104, "views": 0, "votes": 5, "reused": true }, { "id": 165735, "title": "Competition Rules", "comment_count": 38, "views": 0, "votes": 20, "reused": true }, { "id": 148592, "title": "Welcome to the Global Wheat Detection Challenge", "comment_count": 27, "views": 0, "votes": 28, "reused": true }, { "id": 148563, "title": "Looking for a Team Megathread", "comment_count": 145, "views": 0, "votes": 8, "reused": true }, { "id": 163291, "title": "Competition Update", "comment_count": 26, "views": 0, "votes": 26, "reused": true }, { "id": 148873, "title": "Tips to solve submission error", "comment_count": 6, "views": 0, "votes": 17, "reused": true }, { "id": 172418, "title": "1st place solution [MIT-Compliant]", "comment_count": 90, "views": 0, "votes": 239, "reused": true }, { "id": 171428, "title": "Darknet (AlexeyAB) not working (will not build)", "comment_count": 16, "views": 0, "votes": 3, "reused": true }, { "id": 232550, "title": "How to win object detection competetion", "comment_count": 15, "views": 0, "votes": 33, "reused": true }, { "id": 172436, "title": "Investigating YOLOv5 components", "comment_count": 25, "views": 0, "votes": 28, "reused": true }, { "id": 162218, "title": "Understanding weighted boxes fusion", "comment_count": 6, "views": 0, "votes": 10, "reused": true }, { "id": 172405, "title": "What's your best score with yolov5 but you didn't pick", "comment_count": 32, "views": 0, "votes": 9, "reused": true }, { "id": 175927, "title": "Bug in the Leaderboard", "comment_count": 6, "views": 0, "votes": 33, "reused": true }, { "id": 187120, "title": "Advanced Topics", "comment_count": 4, "views": 0, "votes": 16, "reused": true }, { "id": 172440, "title": "Updated lb position 228 ,unselected 15th place ", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 238097, "title": "Update - Global Wheat Challenge 2021 - New version of the dataset !", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 172753, "title": "Yolov5 fine-tuning results", "comment_count": 1, "views": 0, "votes": 10, "reused": true }, { "id": 172569, "title": "[Update ] The 9th place solution with code", "comment_count": 97, "views": 0, "votes": 266, "reused": true }, { "id": 152788, "title": "Problems with offline installation from git repos", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 175961, "title": "2nd Place Solution with Code [MIT-Compliant]", "comment_count": 19, "views": 0, "votes": 106, "reused": true }, { "id": 152368, "title": "EfficientDet Baseline", "comment_count": 22, "views": 0, "votes": 25, "reused": true }, { "id": 207890, "title": "Dataloading issue using FastAI", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 205859, "title": "BBox augmentation?", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 206019, "title": "Datasets that not only detect objects but also classify classes?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 202503, "title": "why there is not many yolov5?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 198878, "title": "Hosting a similar competition", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 170175, "title": "Evaluation for EfficientDet?", "comment_count": 19, "views": 0, "votes": 8, "reused": true }, { "id": 196179, "title": "3 months later, a competition follow-up !", "comment_count": 1, "views": 0, "votes": 8, "reused": true }, { "id": 190691, "title": "The rest test dataset", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 165840, "title": "Getting demotivated by public high scoring kernel", "comment_count": 3, "views": 0, "votes": -6, "reused": true }, { "id": 169117, "title": "Train EfficientDet like YOLO V5(with code)", "comment_count": 51, "views": 0, "votes": 27, "reused": true }, { "id": 176528, "title": "Removed for being honest?", "comment_count": 91, "views": 0, "votes": 323, "reused": true }, { "id": 188025, "title": "Submission CSV Not Found ", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 156997, "title": "Facebook's DE⫶TR: End-to-End Object Detection with Transformers", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 187931, "title": "Submitting YOLOv5 Notebook without internet", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 182536, "title": "EfficientDet Explained", "comment_count": 12, "views": 0, "votes": 27, "reused": true }, { "id": 164602, "title": "Object detection zoology", "comment_count": 6, "views": 0, "votes": 16, "reused": true }, { "id": 160353, "title": "Bug in the dataset", "comment_count": 19, "views": 0, "votes": 66, "reused": true }, { "id": 169053, "title": "can i use CNN in this problem", "comment_count": 2, "views": 0, "votes": -3, "reused": true }, { "id": 182768, "title": "Open the all data set for further research", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 179625, "title": "Git clone --- OFF INTERNET", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 176066, "title": "Does changing dataset setting after the competition close affect the re-run?", "comment_count": 12, "views": 0, "votes": 8, "reused": true }, { "id": 179466, "title": "Which is best data set for beginner ?", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 177757, "title": "Only respond to those who get most votes? This is for those who should not be ignored!", "comment_count": 6, "views": 0, "votes": 20, "reused": true }, { "id": 176041, "title": "Release of test data", "comment_count": 5, "views": 0, "votes": 5, "reused": true }, { "id": 176973, "title": "Conclusion", "comment_count": 21, "views": 0, "votes": 38, "reused": true }, { "id": 157592, "title": "sumbit error:An error occurred while committing kernel: ConcurrencyViolation Draft not found.", "comment_count": 3, "views": 0, "votes": -2, "reused": true }, { "id": 175967, "title": "A summary of compliant submissions which deleted.", "comment_count": 9, "views": 0, "votes": 7, "reused": true }, { "id": 176109, "title": "Thoughts on the large shakeup by the cleaned private set", "comment_count": 12, "views": 0, "votes": 14, "reused": true }, { "id": 176732, "title": "New post-processing trick", "comment_count": 2, "views": 0, "votes": 18, "reused": true }, { "id": 175994, "title": "Delayed submission silver ranked ", "comment_count": 2, "views": 0, "votes": -9, "reused": true }, { "id": 175911, "title": "I became a competition expert :D", "comment_count": 17, "views": 0, "votes": 13, "reused": true }, { "id": 164431, "title": "What's your local validation stats for YoloV5?", "comment_count": 13, "views": 0, "votes": 16, "reused": true }, { "id": 173180, "title": "Sharing yolov5 codes", "comment_count": 7, "views": 0, "votes": 4, "reused": true }, { "id": 176497, "title": "Newbie Question on Late Submissions", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 175922, "title": "Would-be 39th place solution with single model (yolov4) from a first time competitor", "comment_count": 2, "views": 0, "votes": 15, "reused": true }, { "id": 175979, "title": "[34th Place Solution using single EfficientDet + Pseudo Labeling]", "comment_count": 10, "views": 0, "votes": 15, "reused": true }, { "id": 175971, "title": "Nice work Roman ", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 175711, "title": "Can Someone tell me which library is prohibited?", "comment_count": 6, "views": 0, "votes": 7, "reused": true }, { "id": 175662, "title": "Teams with at least 1 yoloV5 should be deleted completely ", "comment_count": 10, "views": 0, "votes": 36, "reused": true }, { "id": 176011, "title": "Thanks Kaggle Team - Our First Medal !!!", "comment_count": 2, "views": 0, "votes": 8, "reused": true }, { "id": 175939, "title": "Sharing my 0.6977 CenterNet training + inference notebooks", "comment_count": 5, "views": 0, "votes": 20, "reused": true }, { "id": 175952, "title": "Why are my compliant submissions deleted？", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 175999, "title": "Huge difference between public and private scores?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 175987, "title": "[Share] Clean BBox Dataset & Competiton Expert", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 175925, "title": "Post-Competition Survey and Feedback", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 175956, "title": "Incorrectly removed?", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 175935, "title": "Deleted Dataset and Medals Question", "comment_count": 5, "views": 0, "votes": 11, "reused": true }, { "id": 174334, "title": "Open-sourcing my final submission kernel", "comment_count": 12, "views": 0, "votes": 49, "reused": true }, { "id": 175932, "title": "Why is this an error? (Using only EffDet5)", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 172415, "title": "Late Submissions", "comment_count": 11, "views": 0, "votes": 2, "reused": true }, { "id": 175905, "title": "Final results are now available", "comment_count": 3, "views": 0, "votes": 7, "reused": true }, { "id": 175915, "title": "Congratulations to Liao, the latest Competitions Grandmaster", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 175907, "title": "Single fold + single scale better than multi-fold + multi scale?", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 175819, "title": "Invalidated for using a prohibited library", "comment_count": 14, "views": 0, "votes": 9, "reused": true }, { "id": 175704, "title": "More manual checking needed for YoloV5?", "comment_count": 3, "views": 0, "votes": 20, "reused": true }, { "id": 175679, "title": "Yolov5 submissions removed?", "comment_count": 4, "views": 0, "votes": 6, "reused": true }, { "id": 175753, "title": "Kudos to Kaggle Team where due - and some Leaderboard insights", "comment_count": 0, "views": 0, "votes": 10 }, { "id": 175752, "title": "Kudos to Kaggle Team where due - and some Leaderboard insights", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 175661, "title": "Belated question on object detection", "comment_count": 1, "views": 0, "votes": 5, "reused": true }, { "id": 172408, "title": "Deleted accounts still hold the medal position？ ", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 175665, "title": "Medal border line was changed !!?????", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175644, "title": "Huge props to the Kaggle team", "comment_count": 2, "views": 0, "votes": 24, "reused": true }, { "id": 175381, "title": "When does the competition end?", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 175621, "title": "I see movemement in the list, OK folks time to hold on to something, here we go.", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 174760, "title": "Please hide \"x days to go\"", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 168353, "title": "Admins, please automatically remove YOLOv5 submissions", "comment_count": 47, "views": 0, "votes": 72, "reused": true }, { "id": 175080, "title": "Please release the clean dataset used in this competition", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 174711, "title": "Tomorrow never dies!", "comment_count": 11, "views": 0, "votes": 17, "reused": true }, { "id": 174783, "title": "Kaggle Prediction Competition", "comment_count": 2, "views": 0, "votes": 11, "reused": true }, { "id": 174749, "title": "Deja vu? So when is the end?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174732, "title": "Day after day, year after year", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 174209, "title": "2 days to go?", "comment_count": 3, "views": 0, "votes": 5, "reused": true }, { "id": 173112, "title": "What should I add to EfficientDet?", "comment_count": 14, "views": 0, "votes": 45, "reused": true }, { "id": 173754, "title": "\"SUBMITTED AFTER DEADLINE\" issue", "comment_count": 26, "views": 0, "votes": 4, "reused": true }, { "id": 173862, "title": "chance to choose submissions again", "comment_count": 2, "views": 0, "votes": -18, "reused": true }, { "id": 173854, "title": "Is this the processing of the new test set?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 173045, "title": "Update on removing non-compliant solutions?", "comment_count": 14, "views": 0, "votes": 19, "reused": true }, { "id": 172473, "title": "YoloV5 Dynamic, Faster, Out of the box and Stronger", "comment_count": 3, "views": 0, "votes": 14, "reused": true }, { "id": 173581, "title": "Ranks have changed!", "comment_count": 20, "views": 0, "votes": 7, "reused": true }, { "id": 172416, "title": "[80th place solution😂] Source-separated Psuedo Labeling", "comment_count": 14, "views": 0, "votes": 42, "reused": true }, { "id": 172404, "title": "[Compliant Solution] Who Is Real Best?!", "comment_count": 26, "views": 0, "votes": 25, "reused": true }, { "id": 162642, "title": "Object Detection with Facebook's Detection Transformer", "comment_count": 7, "views": 0, "votes": 10, "reused": true }, { "id": 172522, "title": "[From 447 to 135th place Solution] EfficientDet Ensemble", "comment_count": 8, "views": 0, "votes": 12, "reused": true }, { "id": 172409, "title": "[42nd place solution]", "comment_count": 30, "views": 0, "votes": 80, "reused": true }, { "id": 172615, "title": "Just when you thought it was over...", "comment_count": 7, "views": 0, "votes": 5, "reused": true }, { "id": 172523, "title": "[129th place Solution] Rare method used with Yolov4", "comment_count": 6, "views": 0, "votes": 10, "reused": true }, { "id": 173153, "title": "Darknet YOLOv4 Inference and Pseudo-label Training on Kaggle GPU Notebook", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 172565, "title": "How does the score calculated?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 172827, "title": "[30th place solution] Weird TTA trick? Detect by quadrant provided a great boost!", "comment_count": 7, "views": 0, "votes": 13, "reused": true }, { "id": 172567, "title": "[16th place solution] ", "comment_count": 22, "views": 0, "votes": 25, "reused": true }, { "id": 172485, "title": "Some tricks worked (just a little) for my CenterNet", "comment_count": 4, "views": 0, "votes": 17, "reused": true }, { "id": 172546, "title": "185th place solution", "comment_count": 6, "views": 0, "votes": 22, "reused": true }, { "id": 168372, "title": "What does the wheat falling on the ground considered as?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 172732, "title": "[340th place Solution] EfficientDet with PLx2", "comment_count": 2, "views": 0, "votes": 8, "reused": true }, { "id": 172459, "title": "Suggestions to future competitions ", "comment_count": 12, "views": 0, "votes": 18, "reused": true }, { "id": 172479, "title": "How/when is the cleaning of non-compliant Submissions done?", "comment_count": 6, "views": 0, "votes": 6, "reused": true }, { "id": 172747, "title": "Compatible version of Wheat-Ears-Detection-Dataset", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 172634, "title": "Submissions have been disabled for this competition", "comment_count": 5, "views": 0, "votes": -2, "reused": true }, { "id": 172494, "title": "When will the final leaderboard come out?", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 172458, "title": "5th Place Solution (EfficientDet)", "comment_count": 12, "views": 0, "votes": 50, "reused": true }, { "id": 172583, "title": "Data generated using Style Transfer and Pix2Pix", "comment_count": 1, "views": 0, "votes": 4, "reused": true }, { "id": 172500, "title": "Did you clean your dataset of faulty bboxes for final submissions?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 171965, "title": "what have u learnt from this competition ?( any experience)", "comment_count": 24, "views": 0, "votes": 13 }, { "id": 172410, "title": "Sharing is caring!", "comment_count": 5, "views": 0, "votes": 5, "reused": true }, { "id": 172433, "title": "Failed EfficientDet Solution", "comment_count": 5, "views": 0, "votes": 7, "reused": true }, { "id": 172497, "title": "Gold Medal Solution Links [PlaceHolder]🏅", "comment_count": 1, "views": 0, "votes": 8, "reused": true }, { "id": 172423, "title": "Are YOLO eliminated?", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 172469, "title": "🎁 Collection: List of Ranked Notebooks and Topics", "comment_count": 2, "views": 0, "votes": 5, "reused": true }, { "id": 171052, "title": "SGDP & AdamP Optimizers", "comment_count": 5, "views": 0, "votes": 13, "reused": true }, { "id": 172432, "title": "Honesty doesn't pay?", "comment_count": 7, "views": 0, "votes": 4, "reused": true }, { "id": 172476, "title": "Have patience. Now the inspection period begins.", "comment_count": 4, "views": 0, "votes": 7, "reused": true }, { "id": 172472, "title": "Thank you to all and rank \"997th\"'s approach", "comment_count": 1, "views": 0, "votes": 6, "reused": true }, { "id": 172372, "title": "[Data Cleaning] Visualization of Clean BBoxs in Images", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 172420, "title": "Will the conclusion be further verified", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 172428, "title": "Congratulations (?) and Great Shake Up Again", "comment_count": 3, "views": 0, "votes": 16, "reused": true }, { "id": 171963, "title": "Should we expect a shake-up?", "comment_count": 25, "views": 0, "votes": 5, "reused": true }, { "id": 172450, "title": "Time for organizers to remove all non-compliant solutions", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 172402, "title": "MASSVE shakeup... From top 100 to 400", "comment_count": 15, "views": 0, "votes": 5, "reused": true }, { "id": 172441, "title": "Some interesting things I tried", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 172442, "title": "UTokyo ratio in the Public set?", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 172395, "title": "List of things that didn't work", "comment_count": 8, "views": 0, "votes": 12, "reused": true }, { "id": 172411, "title": "What is your score except for Yolo5?", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 172419, "title": "normalize bbox?", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 172413, "title": "Congrats to Orkatz2 & Team", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 172378, "title": "We Will Use Compliant Submissions and some observations", "comment_count": 10, "views": 0, "votes": 14, "reused": true }, { "id": 172229, "title": "Some pitfalls with EfficientDet public kernel", "comment_count": 2, "views": 0, "votes": 11, "reused": true }, { "id": 172382, "title": "Sharing my Refined Dataset (Stitched images & manually edited)", "comment_count": 6, "views": 0, "votes": 4, "reused": true }, { "id": 166793, "title": "Leaderboard of Compliant Submissions", "comment_count": 122, "views": 0, "votes": 84, "reused": true }, { "id": 172273, "title": "All the best everyone", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 172380, "title": "How can we use TPU/GPU to run our codes, using tensorflow/keras in Kaggle?", "comment_count": 2, "views": 0, "votes": -2 }, { "id": 172359, "title": "Will YoloV5 Sub be Discarded?", "comment_count": 2, "views": 0, "votes": -6, "reused": true }, { "id": 171521, "title": "CycleGAN Adventures", "comment_count": 11, "views": 0, "votes": 44, "reused": true }, { "id": 172289, "title": "Rapid optimizer and scheduler mix", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 172355, "title": "It can be repeated - choose smart", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 172260, "title": "Looking forward to great sharing", "comment_count": 3, "views": 0, "votes": 5, "reused": true }, { "id": 171987, "title": "How are training notebooks audited?", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 172203, "title": "Choose 2 none-yolo5 subs.", "comment_count": 3, "views": 0, "votes": 25, "reused": true }, { "id": 167140, "title": "Straightforward question: Can I use a solution with non-compliant license to get a medal?", "comment_count": 37, "views": 0, "votes": 55, "reused": true }, { "id": 171715, "title": "Kind Reminder for Submission Compliance", "comment_count": 16, "views": 0, "votes": 45, "reused": true }, { "id": 170810, "title": "We need a clear explanation before the end of the game:)", "comment_count": 24, "views": 0, "votes": 39, "reused": true }, { "id": 171664, "title": "A Question About Time Limitation", "comment_count": 9, "views": 0, "votes": 4, "reused": true }, { "id": 153084, "title": "Best single model", "comment_count": 81, "views": 0, "votes": 37, "reused": true }, { "id": 171805, "title": "Kaggle Error on submission", "comment_count": 6, "views": 0, "votes": 5, "reused": true }, { "id": 171978, "title": "No submit button for notebook", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 172100, "title": "Idea to check compliant solutions", "comment_count": 8, "views": 0, "votes": 9, "reused": true }, { "id": 164627, "title": "Submission Scoring Error", "comment_count": 16, "views": 0, "votes": 2, "reused": true }, { "id": 170898, "title": "submit error，too cruel for beginners", "comment_count": 31, "views": 0, "votes": 2, "reused": true }, { "id": 149871, "title": "Submission scoring error/submission CSV not found", "comment_count": 29, "views": 0, "votes": 24, "reused": true }, { "id": 151805, "title": " Status: Submission CSV Not Found & Public Score: Error", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 171595, "title": "A runtime error occurred recently: Interger division of tensors use div ...", "comment_count": 7, "views": 0, "votes": 8, "reused": true }, { "id": 152066, "title": "Problems with submitting the submission file", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 172046, "title": "Are non-built-in optimizers part of External Data?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 168932, "title": "Is there an effective method to evaluate a model?", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 170973, "title": "Submission stuck", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 171832, "title": "How many Test Images", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 171823, "title": "Dear Organizers, Please Double-Check Your Private Dataset's Edges", "comment_count": 1, "views": 0, "votes": 6, "reused": true }, { "id": 170771, "title": "Why Pseudo Labeling is not working well with EffDet?", "comment_count": 22, "views": 0, "votes": 12, "reused": true }, { "id": 171780, "title": "Pytorch progress bar in Colab = Tqdm", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 171702, "title": "Duplicates during ensembling", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 171684, "title": "Purpose of iou th", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 171617, "title": "Why best loss can't get good lb", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 167383, "title": "A Small Inquiry", "comment_count": 10, "views": 0, "votes": 19, "reused": true }, { "id": 169272, "title": "Weird LB Score - DETR", "comment_count": 12, "views": 0, "votes": 2, "reused": true }, { "id": 162462, "title": "YOLOv5 Pseudo Labeling", "comment_count": 59, "views": 0, "votes": 54, "reused": true }, { "id": 159883, "title": "What worked for me", "comment_count": 34, "views": 0, "votes": 85, "reused": true }, { "id": 171528, "title": "Prebuilt YOLOv4 Darknet on Kaggle GPU Notebook", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 170102, "title": "/bin/sh: 1: ./darknet: Permission denied error", "comment_count": 13, "views": 0, "votes": 1, "reused": true }, { "id": 171009, "title": "Are any top teams using yolov4? How much improvement does PL/OOF give?", "comment_count": 8, "views": 0, "votes": 1, "reused": true }, { "id": 171006, "title": "New EfficientDet-D7x", "comment_count": 11, "views": 0, "votes": 10, "reused": true }, { "id": 170734, "title": "To switch from Adam to SGD may improve some performance...", "comment_count": 27, "views": 0, "votes": 7, "reused": true }, { "id": 171263, "title": "Can we submit two or more at the same time (with pseudo labeling) ? ", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 170744, "title": "Low yolov4 performance compared to yolov5", "comment_count": 11, "views": 0, "votes": 2, "reused": true }, { "id": 170849, "title": "Is it possible to build OpenCV from github branch in Kaggle Kernel?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 171057, "title": "A question on the EfficientDet public kernel", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 153807, "title": "How can I convert the csv to a coco format json", "comment_count": 4, "views": 0, "votes": 3 }, { "id": 163750, "title": "tricks for solving submission error", "comment_count": 9, "views": 0, "votes": 10, "reused": true }, { "id": 170888, "title": "Optimizer: Rectified Adam (RAdam). Improve your AI accuracy", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 170500, "title": "Submission error", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 170326, "title": "Non post-processed LB scores with single fold models? Especially FasterRCNN.", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 170263, "title": "Will there be shakeup?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 170974, "title": "NVIDIA Apex", "comment_count": 5, "views": 0, "votes": 9, "reused": true }, { "id": 170269, "title": "Unable to Submit to Competition", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 163235, "title": "any suggestion for this error", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 168649, "title": "How many efficientDet epochs are you running?", "comment_count": 15, "views": 0, "votes": 2, "reused": true }, { "id": 170701, "title": "Hosts & kaggle Team: Is Sub Using Test data Trained Model Allowed", "comment_count": 0, "views": 0, "votes": -1 }, { "id": 170562, "title": "Kaggle Error", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 164346, "title": "Additional Training Examples (wheat spikes )", "comment_count": 22, "views": 0, "votes": 15, "reused": true }, { "id": 170283, "title": "Does COCO dataset and COCO based pretrained models allowed?", "comment_count": 4, "views": 0, "votes": 8, "reused": true }, { "id": 155144, "title": "Validation's mAP so different from public LB's mAP?", "comment_count": 15, "views": 0, "votes": 7, "reused": true }, { "id": 170335, "title": "Someone posted charts of OOF validation per source. Anyone know where they are?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 169666, "title": " TensorFlow and Keras version Problem ", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 160940, "title": "Anyone getting worse results when combining TTA x model ensembles?", "comment_count": 16, "views": 0, "votes": 14, "reused": true }, { "id": 170324, "title": "LB without Yolov5", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 168822, "title": "Something weird", "comment_count": 11, "views": 0, "votes": null, "reused": true }, { "id": 170211, "title": "Yet-Another-EfficientDet-Pytorch", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 170126, "title": "Submission Format", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 170136, "title": "Retina-Net", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 160408, "title": "Speeding up the training process with a simple trick", "comment_count": 10, "views": 0, "votes": 70, "reused": true }, { "id": 169771, "title": "Best tips for object detection/segmentation", "comment_count": 1, "views": 0, "votes": -2, "reused": true }, { "id": 168199, "title": "Gradient accumulation", "comment_count": 37, "views": 0, "votes": 7, "reused": true }, { "id": 169045, "title": "Finetuning Faster RCNN backbone", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 156906, "title": "PyTorch faster RCNN => NaN loss", "comment_count": 11, "views": 0, "votes": 2, "reused": true }, { "id": 169777, "title": "Your thought about WBF vs NMS?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 169692, "title": "What lr should choose?", "comment_count": 9, "views": 0, "votes": 1, "reused": true }, { "id": 161968, "title": "Tips/Tricks for speeding up training/inference", "comment_count": 8, "views": 0, "votes": 9, "reused": true }, { "id": 169744, "title": "Is Mixup improving your results?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 169922, "title": "Submission each day after teamup", "comment_count": 0, "views": 0, "votes": -7 }, { "id": 169823, "title": "Huge Weight Size with Eff det", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 169739, "title": "How to install additional libraries", "comment_count": 10, "views": 0, "votes": null, "reused": true }, { "id": 169866, "title": "RuntimeError: Error(s) in loading state_dict for EfficientDet", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 169824, "title": "Simple trick/solution for Submission CSV Not Found issue", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 169787, "title": "About the time limit for kernels", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 169804, "title": "Yolov5 0.74+ LB reproducibility [learning purposes]", "comment_count": 0, "views": 0, "votes": -2 }, { "id": 169264, "title": "I'm beginner, could you answer some my question? ", "comment_count": 8, "views": 0, "votes": 1, "reused": true }, { "id": 169600, "title": "Understanding WBF", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 169228, "title": "submission.csv not found - why not?", "comment_count": 5, "views": 0, "votes": 5, "reused": true }, { "id": 169311, "title": "Any idea about data clean", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 159578, "title": "List of images with bboxes without wheat.", "comment_count": 24, "views": 0, "votes": 59, "reused": true }, { "id": 169528, "title": "about entry deadline.", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 167333, "title": "Data Cleaning", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 167624, "title": "Issue with Submission. Help please!", "comment_count": 29, "views": 0, "votes": 4, "reused": true }, { "id": 169197, "title": "Validation /Train Split strategy", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 165393, "title": "can anyone kindly describe about the bbox column?", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 169223, "title": "How to avoid bias?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 169468, "title": "About submitting", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 167554, "title": "YoloV5 is giving better results with out tweaking it much because", "comment_count": 23, "views": 0, "votes": 19, "reused": true }, { "id": 167375, "title": "This competition after YoloV5 is banned [meme]", "comment_count": 8, "views": 0, "votes": 32, "reused": true }, { "id": 169427, "title": "Submission Scoring Error - Sample Submission", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 168727, "title": "Score not improving.", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 169276, "title": "No module named 'utils.datasets'", "comment_count": 1, "views": 0, "votes": -2, "reused": true }, { "id": 148754, "title": "Pytorch FasterRCNN starter", "comment_count": 7, "views": 0, "votes": 29, "reused": true }, { "id": 165414, "title": "Is YOLO-V5 worse than YOLO-V4 ?", "comment_count": 7, "views": 0, "votes": 3, "reused": true }, { "id": 168957, "title": "Looking for a team. I am beginner", "comment_count": 2, "views": 0, "votes": null }, { "id": 168934, "title": "target value ", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 168880, "title": "get more results but low scores?", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 168579, "title": "Yolo is not that much better. It was just used for automatic LABELING", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 163433, "title": "Hosts answer needed : GPL-3 licence on YoloV5", "comment_count": 90, "views": 0, "votes": 53, "reused": true }, { "id": 166564, "title": "Some of my observations", "comment_count": 10, "views": 0, "votes": 48, "reused": true }, { "id": 164818, "title": "License Comparison: MIT vs GPLv3.0", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 165843, "title": "How to train the model on my own computer and submit test results on kaggle?", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 168324, "title": "Is there any minimum confidence level for detection?", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 153590, "title": "project submission", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 167312, "title": "Will the private test set be released after final deadline?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 150492, "title": "Wheat bbox", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 160218, "title": "WHICH ALGORITHM DOES BETTER?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 162332, "title": "ResNeSt", "comment_count": 1, "views": 0, "votes": 3, "reused": true }, { "id": 168508, "title": "Do we have to run this on kaggle notebooks?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 162894, "title": "Submission Error: CSV Not Found", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 168532, "title": "How to do k-fold validate in object detection?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 149770, "title": "Number of samples in test (by source)", "comment_count": 7, "views": 0, "votes": 31, "reused": true }, { "id": 167006, "title": "submission problem.", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 167954, "title": "Can any one offer some help?", "comment_count": 10, "views": 0, "votes": 1, "reused": true }, { "id": 163646, "title": "Has anyone tweaked YOLOv5 model and parameters?", "comment_count": 8, "views": 0, "votes": 3, "reused": true }, { "id": 167125, "title": "EfficientDet", "comment_count": 15, "views": 0, "votes": 1, "reused": true }, { "id": 167092, "title": "[New] Best Single Model", "comment_count": 12, "views": 0, "votes": 6, "reused": true }, { "id": 168336, "title": "What about LGPL?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 167867, "title": "logs for 'Submission CSV Not Found' error", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 149847, "title": "Submission CSV Not Found", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 168179, "title": "Two small tricks for Submission ERROR", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 168021, "title": "How long is an epoch of Yolo v5 training?", "comment_count": 1, "views": 0, "votes": -6, "reused": true }, { "id": 167960, "title": "How to improve the LB score?", "comment_count": 9, "views": 0, "votes": 1, "reused": true }, { "id": 148690, "title": "Review of Deep Learning Algorithms for Object Detection", "comment_count": 5, "views": 0, "votes": 16, "reused": true }, { "id": 167817, "title": "Image size of the test datasets", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 167535, "title": "\"What is prediction string actually\"", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 167538, "title": "Feasible model for this competition?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 164845, "title": "To anyone using YoloV5, torchvision, etc: a warning about licensing", "comment_count": 46, "views": 0, "votes": 38, "reused": true }, { "id": 167400, "title": "Submisison wheat test", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 167344, "title": "Competition Compliant Train PipeLine", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 167074, "title": "I am confused - yolov5 under MIT licence", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 153971, "title": "What's the meaning of this error after ~4 hours of GPU training?", "comment_count": 1, "views": 0, "votes": 5, "reused": true }, { "id": 166435, "title": "guidance required !!!", "comment_count": 2, "views": 0, "votes": -2, "reused": true }, { "id": 165525, "title": "Can we use yolov4 in this competition?", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 167002, "title": "On Licensing -- Clarity, please Kaggle", "comment_count": 5, "views": 0, "votes": 64, "reused": true }, { "id": 166763, "title": "Questions about the Licences and the Leaderboard", "comment_count": 7, "views": 0, "votes": 3, "reused": true }, { "id": 166845, "title": "Filenames like 4.22E+49 , 4.87E+13 , 30314634 etc. present in csv", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 152260, "title": "Images with no detected wheatheads", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 154524, "title": "GPU is not getting used", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 166508, "title": "Issue while installing whl files on Collab. Help Needed.", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 166830, "title": "Load Weights trained on local machine to kaggle notebook", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 166693, "title": "Submission Scoring Error", "comment_count": 2, "views": 0, "votes": 5, "reused": true }, { "id": 164611, "title": "how commit a kernel in google colab ?😳 ", "comment_count": 4, "views": 0, "votes": null }, { "id": 166075, "title": "YOLO 'tensorflow.python.keras.engine.base_layer_v1", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 160913, "title": "Can't solve error 'Submission CSV Not Found'", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 164140, "title": "Some insights", "comment_count": 7, "views": 0, "votes": 65, "reused": true }, { "id": 165324, "title": "Yolo with small objects", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 165001, "title": "Simple Inference Object Detection with Transformers:DETR", "comment_count": 2, "views": 0, "votes": 7, "reused": true }, { "id": 166408, "title": "collate_fn in pytorch", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 165931, "title": "colab epoch duration issue", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 163112, "title": "Is the Pub LB based only on the 10 test images?", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 163455, "title": "pseudo labeling overfit for test?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 165664, "title": "Adding TTA improved my base model, but after Pseudo Labaling LB decreased", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 154458, "title": "Training on Colab", "comment_count": 12, "views": 0, "votes": 2, "reused": true }, { "id": 166254, "title": "Some questions about competition relus", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 166054, "title": "Huge gap between local validation score and LB", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 149842, "title": "just some easy use augumented dataset", "comment_count": 8, "views": 0, "votes": 4, "reused": true }, { "id": 153257, "title": "Mixup Approach", "comment_count": 10, "views": 0, "votes": 17, "reused": true }, { "id": 164789, "title": "Submission failed", "comment_count": 9, "views": 0, "votes": null, "reused": true }, { "id": 158915, "title": "[PyTorch] Calling Model leads to CUDA OOM ", "comment_count": 19, "views": 0, "votes": 1, "reused": true }, { "id": 165755, "title": "Problem inferencing the model(.pb file)", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 165736, "title": "TF Object Detection API officially supports TensorFlow 2", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 165294, "title": "Leaderboard Paradox", "comment_count": 19, "views": 0, "votes": 12, "reused": true }, { "id": 165500, "title": "Basic questions about the metric", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 165424, "title": "PROPOSAL: Lady's / Gentleman's agreement to add [compliant] tag to team name", "comment_count": 8, "views": 0, "votes": 15, "reused": true }, { "id": 157048, "title": "hi,everone,there is a submission error after l click to submit button,someone can help me and answer what problem in my submission file,l really need some answer,thanks.", "comment_count": 8, "views": 0, "votes": -3, "reused": true }, { "id": 165644, "title": "What should I do? (About current issues)", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 164777, "title": "Issue in calling pytorch version 1.2.0 ", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 153996, "title": "New to kaggle", "comment_count": 3, "views": 0, "votes": -2, "reused": true }, { "id": 165328, "title": "Pseudo labelling", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 161238, "title": "Exploratory Discussion Analysis: Noise in data", "comment_count": 3, "views": 0, "votes": 7, "reused": true }, { "id": 165429, "title": "Unable to load the data into memory", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 165404, "title": "The weighted boxes fusion repo has no license at all", "comment_count": 3, "views": 0, "votes": 5, "reused": true }, { "id": 158371, "title": "YOLOv5 is Here", "comment_count": 9, "views": 0, "votes": 9, "reused": true }, { "id": 158564, "title": "Is anyone using Yolo here ? If yes, please reply to this thread. I need some help !!!", "comment_count": 10, "views": 0, "votes": null }, { "id": 165287, "title": "Leaf-GP", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 165110, "title": "A thought about the Winning Solution", "comment_count": 1, "views": 0, "votes": 6, "reused": true }, { "id": 165076, "title": "Pascal VOC format.", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 164850, "title": "Faster Weighted Boxes Ensembling", "comment_count": 1, "views": 0, "votes": 4, "reused": true }, { "id": 164687, "title": "Submission error", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 164962, "title": "Can we use BatchNorm even though its patented?", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 164954, "title": "free copy for a limited time Deep Learning with PyTorch", "comment_count": 4, "views": 0, "votes": 8, "reused": true }, { "id": 164439, "title": "How to make my own train.csv file from my image dataset?", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 163645, "title": "Test Set Same Distribution?", "comment_count": 10, "views": 0, "votes": 1, "reused": true }, { "id": 152143, "title": "Using TPU for training with PyTorch", "comment_count": 5, "views": 0, "votes": 1, "reused": true }, { "id": 149949, "title": "Test images are not all 1024px by 1024px", "comment_count": 20, "views": 0, "votes": 11, "reused": true }, { "id": 161541, "title": "Literature on Domain Generalization", "comment_count": 1, "views": 0, "votes": 14, "reused": true }, { "id": 164623, "title": "Pre-tuned weights from long hours training are allowed?", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 164090, "title": "Clarification about CV", "comment_count": 13, "views": 0, "votes": 1, "reused": true }, { "id": 164553, "title": "Faster-RCCN: which pre-processing better not to use", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 164409, "title": "After augmentations got worse results based on yoloV5", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 164211, "title": "Notebook Exceeded Allowed Compute Error", "comment_count": 10, "views": 0, "votes": 3, "reused": true }, { "id": 162495, "title": "Unexpected LB score ", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 163679, "title": "train loss larger than valid loss", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 160636, "title": "How to use yolo?", "comment_count": 39, "views": 0, "votes": null, "reused": true }, { "id": 161849, "title": "OpenCv Crash. cv2.imshow", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 163760, "title": "Training pipeline to get > 0.76 LB score", "comment_count": 9, "views": 0, "votes": 24, "reused": true }, { "id": 163964, "title": "labelling YOLO data set", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 164006, "title": "TTA for fasterrcnn", "comment_count": 11, "views": 0, "votes": 7, "reused": true }, { "id": 164172, "title": "DataAugmentation with BBAug", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 164107, "title": "Incomplete data download when using Kaggle api in Colab", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 163896, "title": "Precision metric in this competition ", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 164060, "title": "How to use the GPU training model provided by kaggle?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 163502, "title": "Some Noobie Doubts about Object Detection", "comment_count": 6, "views": 0, "votes": 6, "reused": true }, { "id": 163927, "title": "Weekend reading...", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 163834, "title": "YOLOv5: How do you write data during training?", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 149139, "title": "Useful Papers for detection ", "comment_count": 8, "views": 0, "votes": 27, "reused": true }, { "id": 163642, "title": "Colabs Pro disconnection issues", "comment_count": 10, "views": 0, "votes": 1, "reused": true }, { "id": 149805, "title": "Jigsaw puzzle in train", "comment_count": 17, "views": 0, "votes": 47, "reused": true }, { "id": 163766, "title": "Efficientdet in keras", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 163466, "title": "WBF params overfit?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 163565, "title": "I am confuse with current status of the competition and public leaderboard", "comment_count": 10, "views": 0, "votes": 4, "reused": true }, { "id": 163702, "title": "Broken Link for Code Requirements", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 163551, "title": "About different object detection algo", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 163639, "title": "Looking for a team.", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 163263, "title": "Another issue with labels", "comment_count": 5, "views": 0, "votes": 10, "reused": true }, { "id": 163574, "title": "Submission Problem", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 163420, "title": "Competition update and a token of gratitude on reaching second spot", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 163518, "title": "Re-training from checkpoint issue... YOLOv5", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 163095, "title": "Speed Improvement with Weighted Box Fusion Ver. 1.0.4", "comment_count": 8, "views": 0, "votes": 28, "reused": true }, { "id": 161296, "title": "Treating！！！！", "comment_count": 28, "views": 0, "votes": 16, "reused": true }, { "id": 150120, "title": "Images downloaded with the API are not correct", "comment_count": 4, "views": 0, "votes": 6, "reused": true }, { "id": 162947, "title": "giou loss question", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 163387, "title": "Broken link", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 163102, "title": "Split by location", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 157009, "title": "Label noise", "comment_count": 16, "views": 0, "votes": 32, "reused": true }, { "id": 163215, "title": "Can any explain this two rules", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 163278, "title": "Submission Error", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 159585, "title": "Competition Hosts' Lack of Interaction", "comment_count": 14, "views": 0, "votes": 50, "reused": true }, { "id": 152423, "title": "Using negative samples in FasterRCNN", "comment_count": 2, "views": 0, "votes": 12, "reused": true }, { "id": 162892, "title": "Able to download a small file but not able to download huge(in size)weights.pt file from kaggle", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 163042, "title": " Can anyone explain why my yolov5x model hangs during training", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 158622, "title": "Tensorflow for object detection", "comment_count": 20, "views": 0, "votes": 9, "reused": true }, { "id": 162899, "title": "Data Preprocessing for the TensorflowAPI", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 162648, "title": "The difference between private and public", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 162798, "title": "All in One yolov5 wheat Dataset", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 162572, "title": "What is the size of the final evaluation dataset?", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 162323, "title": "anyone can join team ?", "comment_count": 0, "views": 0, "votes": -10 }, { "id": 162300, "title": "Not able to downgrade tensorflow-gpu to 1.15", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 162247, "title": "Jigsaw puzzle: restore original full-size image", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 162064, "title": "How can we import a compiled .so package of Yolov4?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 162054, "title": "Submission Scoring Error", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 159747, "title": "Highest score using fastrcnn resnet backbone", "comment_count": 18, "views": 0, "votes": 1, "reused": true }, { "id": 160534, "title": "Converting DetectoRS available code to TF2.x ", "comment_count": 1, "views": 0, "votes": -9, "reused": true }, { "id": 161767, "title": "Notebook Exceeded Allowed Compute", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 151577, "title": "Notebook Exceeded Allowed Compute", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 161494, "title": "Similar Dataset and Tutorials to the Competition", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 161606, "title": "Submission CSV Not Found", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 161656, "title": "How to install maskrcnn-benchmark from github?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 161081, "title": "What will be the actual size of test data for final evaluation?", "comment_count": 8, "views": 0, "votes": 4, "reused": true }, { "id": 161483, "title": "ensemble_boxes", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 152866, "title": "Difference between pretrained model and backbone in RCNN", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 160485, "title": "Low Public Score ", "comment_count": 8, "views": 0, "votes": 1, "reused": true }, { "id": 159491, "title": "Correct way to import trained weights", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 160710, "title": "Can I submit from a google colab notebook?", "comment_count": 2, "views": 0, "votes": -1, "reused": true }, { "id": 160859, "title": "DetectoRs dataset for coco format ", "comment_count": 1, "views": 0, "votes": 8, "reused": true }, { "id": 148815, "title": "Global Wheat Detection Sources.", "comment_count": 6, "views": 0, "votes": 6, "reused": true }, { "id": 150781, "title": "Petition to modify the competition evaluation metric", "comment_count": 8, "views": 0, "votes": 21, "reused": true }, { "id": 159994, "title": "Is mmdetection allowed in this competition？", "comment_count": 2, "views": 0, "votes": -2, "reused": true }, { "id": 154685, "title": "Will the big bboxes be fixed?", "comment_count": 4, "views": 0, "votes": 17, "reused": true }, { "id": 148678, "title": "submission.csv Format", "comment_count": 23, "views": 0, "votes": 6, "reused": true }, { "id": 151783, "title": "augmentation techniques", "comment_count": 5, "views": 0, "votes": 26, "reused": true }, { "id": 160247, "title": "External opensource code", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 160021, "title": "How to convert annotation to COCO format？", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 159960, "title": "How to get started after loading the train data?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154994, "title": "YOLOv4 + Poly-YOLO?", "comment_count": 4, "views": 0, "votes": 13, "reused": true }, { "id": 157258, "title": "Error analysis", "comment_count": 3, "views": 0, "votes": 25, "reused": true }, { "id": 159767, "title": "Competition metric", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 150376, "title": "how much Pseudo Labeling contributes to your LB?", "comment_count": 20, "views": 0, "votes": 23, "reused": true }, { "id": 158947, "title": "A reminder to always make your kernels reproducible!", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 159073, "title": "Hardware being used?", "comment_count": 7, "views": 0, "votes": 2, "reused": true }, { "id": 159049, "title": "how do you submit your notebook for the competition?", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 156466, "title": "New SOTA with DetectoRS", "comment_count": 14, "views": 0, "votes": 42, "reused": true }, { "id": 155468, "title": "NaN NaN NaN!!!", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 158766, "title": "[newbie] workflow", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 158889, "title": "Correct way to do image augmentations", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 158749, "title": "Can you share how to use tensorflow's official EfficientDet？", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 152491, "title": "submission scoring error", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 158345, "title": "Bounding Box Dimensions", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 158305, "title": "Copying file from input to kaggle/working", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 154373, "title": "[Bayesian optimization WBF] EfficientDet", "comment_count": 15, "views": 0, "votes": 42, "reused": true }, { "id": 158107, "title": "I can't submit", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 157778, "title": "Submission Scoring Error", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 149458, "title": "Some things to consider.", "comment_count": 2, "views": 0, "votes": 7, "reused": true }, { "id": 155178, "title": "has it only 10 images for test?", "comment_count": 2, "views": 0, "votes": -5 }, { "id": 157693, "title": "Submission scoring takes too much time", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 148575, "title": "Plant Object Detection / Counting Papers", "comment_count": 14, "views": 0, "votes": 46, "reused": true }, { "id": 157393, "title": "Metric calculation", "comment_count": 5, "views": 0, "votes": 1, "reused": true }, { "id": 152846, "title": "High Scoring Public Kernels", "comment_count": 39, "views": 0, "votes": 21, "reused": true }, { "id": 156489, "title": "[WBF over TTA][Single Model] EfficientDet", "comment_count": 10, "views": 0, "votes": 17, "reused": true }, { "id": 156437, "title": "How to evaluate my model without submission?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 157051, "title": "hi,everone,there is a submission error after l click to submit button,someone can help me and answer what problem in my submission file,l really need some answer,thanks.", "comment_count": 0, "views": 0, "votes": -1 }, { "id": 156825, "title": "How long does it take to commmit your code", "comment_count": 7, "views": 0, "votes": -2, "reused": true }, { "id": 156874, "title": "Kaggle mAP formula vs. Standard mAP formula", "comment_count": 3, "views": 0, "votes": 10, "reused": true }, { "id": 152010, "title": "Implement baseline methods with MMDetection", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 149207, "title": "Submission takes too much time", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 152540, "title": "about submit online environment", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154983, "title": "[COCO v.s. ImageNet v.s. Others] What Pretrained Backbone You Use?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 149529, "title": "CV vs LB score", "comment_count": 27, "views": 0, "votes": 22, "reused": true }, { "id": 156562, "title": "Submission error : Notebook Exceeded Allowed Compute", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 149809, "title": "Submission csv not found", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 154071, "title": "Transformers for object detection from Facebook", "comment_count": 10, "views": 0, "votes": 33, "reused": true }, { "id": 155100, "title": "confusion about submission scoring errors", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 155933, "title": "Is the test data split stratified?", "comment_count": 3, "views": 0, "votes": 4, "reused": true }, { "id": 154090, "title": "Youtube Tutorial", "comment_count": 5, "views": 0, "votes": 6, "reused": true }, { "id": 155900, "title": "Understanding and problem definition", "comment_count": 2, "views": 0, "votes": -2 }, { "id": 154613, "title": "submit got 404", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 155758, "title": "Training model locally - question", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154505, "title": "Rcnn", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 155475, "title": "What is the time limit in submission", "comment_count": 2, "views": 0, "votes": -2, "reused": true }, { "id": 148715, "title": "Code Competition Doubts", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 152864, "title": "Using colab", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 155195, "title": "Just to clarify, if we train a model and upload it to Kaggle to use in a test kernel,", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 154774, "title": "Tiny bboxes", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 154932, "title": "Simple way to visualize images and metadata", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 154199, "title": "Unable to submit !", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 154721, "title": "Does GPU submission time count towards your quota?", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 154576, "title": "idea color conversion", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 149032, "title": "Are huge bboxes normal?", "comment_count": 16, "views": 0, "votes": 41, "reused": true }, { "id": 152459, "title": "How to ensemble models after k fold cross validation in object detection task", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 151800, "title": "Cutout Augmentation with handling of bounding boxes", "comment_count": 7, "views": 0, "votes": 7, "reused": true }, { "id": 153923, "title": "About submission error", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 154078, "title": "Vertical & Horizontal Flip using Albumentation", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 151768, "title": "How were the test data splitted ?", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 154057, "title": "I could run my script successfully but when I run&commit, it notified the error \"no module name...\" (I tried to use some libraries such as imutils...))", "comment_count": 1, "views": 0, "votes": null }, { "id": 152851, "title": "Upload Model via Google Colab?", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 153899, "title": "Please Help me, 【ValueError: No ground-truth boxes available for one of the images during training】", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 152053, "title": "Tricks that can help improve model performance", "comment_count": 33, "views": 0, "votes": 18, "reused": true }, { "id": 153639, "title": "Pre-trained model.", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 149747, "title": "Should I run albumentations on both train and valid?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 153536, "title": "Why augmenting data on the fly is better approach than creating a new larger dataset? [solved]", "comment_count": 5, "views": 0, "votes": 1, "reused": true }, { "id": 149896, "title": "求队友Looking for partner, I have a 2070 GPU", "comment_count": 15, "views": 0, "votes": null, "reused": true }, { "id": 152581, "title": "Different Packages Vers for Google Colab and Kaggle", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 153382, "title": "How to annotate the public test images?", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 153194, "title": "How to load model without Internet access?", "comment_count": 7, "views": 0, "votes": 2, "reused": true }, { "id": 153191, "title": "How to deal with images with no object? (Apart form removing them)", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 153077, "title": "How to make submission", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 149620, "title": "New to Object Detection-Please Help!!", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 148950, "title": "Basic image EDA tool", "comment_count": 6, "views": 0, "votes": 11, "reused": true }, { "id": 152569, "title": "How To Prepare A Stratified Split", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 152595, "title": "Please Help me,Got a astonishing error", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 151495, "title": "How we can use Detectron2?", "comment_count": 9, "views": 0, "votes": 3, "reused": true }, { "id": 150780, "title": "Different detector solution's performance(Keep updated...)", "comment_count": 12, "views": 0, "votes": 21, "reused": true }, { "id": 152019, "title": "Beginner question regards using inference and training notebooks", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 152258, "title": "test all data augmentation functions of albumentations", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 150270, "title": "Data Augmentation for object detection experiments ", "comment_count": 18, "views": 0, "votes": 6, "reused": true }, { "id": 152045, "title": "Difficulty in understanding sample_submission", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 151779, "title": "Hyperparameter Search using Weights and Biases", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 149148, "title": "[competition host] question about pseudo labeling", "comment_count": 7, "views": 0, "votes": 24, "reused": true }, { "id": 151595, "title": "Anchor boxes count", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 151215, "title": "A GitHub repo having all approaches and code I've tried so far", "comment_count": 5, "views": 0, "votes": 8, "reused": true }, { "id": 151400, "title": "Limit about CPU, GPU", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 150972, "title": "How to train faster-RCNN with different backbones?", "comment_count": 8, "views": 0, "votes": 6, "reused": true }, { "id": 150951, "title": "WBF approach", "comment_count": 3, "views": 0, "votes": 24, "reused": true }, { "id": 150532, "title": "Surprising consistency in training curves (FPN-Faster-RCNN, PyTorch))", "comment_count": 3, "views": 0, "votes": 4, "reused": true }, { "id": 149008, "title": "Hello everyone, I can't find the \"Commit\" button in the notebook interface when I submit the result file. What's the matter, can someone answer my question? Thank you", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 150663, "title": "This leaderboard is calculated with approximately 62% of the test data.", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 149723, "title": "GPU quota", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 149527, "title": "Is YOLOV3 effective ？", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 150526, "title": "How train Fast rcnn on Multi GPUs?", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 150408, "title": "Augmentations and some simple bounding box plots helper functions and sanity check on data", "comment_count": 2, "views": 0, "votes": 10, "reused": true }, { "id": 149630, "title": "New to kaggle,help!", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 150142, "title": "Does anyone have a sense of how classification probability threshold impacts final score?", "comment_count": 3, "views": 0, "votes": 3, "reused": true }, { "id": 149447, "title": "quick submission", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 149548, "title": "New to Kaggle, Help!!", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 149929, "title": "Scope of One-Stage Detector?", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 149562, "title": "Useful metadata including photo locations, plant maturity, genotypes, and camera specs", "comment_count": 5, "views": 0, "votes": 8, "reused": true }, { "id": 149673, "title": "My notebook keep restarting just when I read the image", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 149070, "title": "k fold cross validation with images", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 148898, "title": "Anyone using TensorFlow Object Detection API for this challenge?", "comment_count": 1, "views": 0, "votes": null }, { "id": 149214, "title": "Can we ignore colour?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 149204, "title": "A repo with better structured version of my kernel", "comment_count": 3, "views": 0, "votes": 6, "reused": true }, { "id": 149211, "title": "Detecting with CenterNets", "comment_count": 1, "views": 0, "votes": 4, "reused": true }, { "id": 149169, "title": "Metric & Model Validation", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 148989, "title": "Research Articles with Network Architectures related to Wheat Head Detection ", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 149176, "title": "Plethora of pytorch pretrained models", "comment_count": 1, "views": 0, "votes": 4, "reused": true }, { "id": 149103, "title": "Sub-categorization in Object Detection", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 148557, "title": "Recent webinar on this Challenge", "comment_count": 4, "views": 0, "votes": 28, "reused": true }, { "id": 148859, "title": "A Bit of Motivation - The Age of A.I.", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 148851, "title": "Competition metric details + script", "comment_count": 0, "views": 0, "votes": 10 }, { "id": 148829, "title": "Submission completion notifications", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 148696, "title": "Validation strategies - kRegionsOut", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 148570, "title": "Latest Detection Papers", "comment_count": 1, "views": 0, "votes": 22, "reused": true } ], "errors": [] }