📄 āļĢāļēāļĒāļĨāļ°āđ€āļ­āļĩāļĒāļ”āļ‚āđ‰āļ­āļĄāļđāļĨ (Dataset Description) Objective: To classify images into two categories: Muffin and Chihuahua. (āļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļˆāļģāđāļ™āļāļĢāļđāļ›āļ āļēāļžāļ­āļ­āļāđ€āļ›āđ‡āļ™ 2 āļ›āļĢāļ°āđ€āļ āļ— āļ„āļ·āļ­ āļĄāļąāļŸāļŸāļīāļ™ āđāļĨāļ° āļŠāļīāļ§āļēāļ§āļē) Content: The dataset contains high-quality images of blueberry muffins and chihuahua dogs in various poses. These images are visually similar, making it a perfect case study for fine-grained feature extraction. (āļŠāļļāļ”āļ‚āđ‰āļ­āļĄāļđāļĨāļ›āļĢāļ°āļāļ­āļšāļ”āđ‰āļ§āļĒāļĢāļđāļ›āļ āļēāļžāļ„āļļāļ“āļ āļēāļžāļŠāļđāļ‡āļ‚āļ­āļ‡āļĄāļąāļŸāļŸāļīāļ™āļšāļĨāļđāđ€āļšāļ­āļĢāđŒāļĢāļĩāđˆāđāļĨāļ°āļŠāļļāļ™āļąāļ‚āļžāļąāļ™āļ˜āļļāđŒāļŠāļīāļ§āļēāļ§āļēāđƒāļ™āļŦāļĨāļēāļāļŦāļĨāļēāļĒāļ—āđˆāļēāļ—āļēāļ‡ āļ‹āļķāđˆāļ‡āļĄāļĩāļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āļāļąāļ™āļ—āļēāļ‡āļāļēāļĒāļ āļēāļžāļŠāļđāļ‡ āđ€āļŦāļĄāļēāļ°āļŠāļģāļŦāļĢāļąāļšāļāļēāļĢāļ—āļ”āļŠāļ­āļšāļāļēāļĢāļ”āļķāļ‡āļĨāļąāļāļĐāļ“āļ°āđ€āļ”āđˆāļ™āđ€āļŠāļīāļ‡āļĨāļķāļ) Data Structure: Total Images: 5,917 files (āđāļšāđˆāļ‡āđ€āļ›āđ‡āļ™ Train 80% āđāļĨāļ° Test 20%) Format: Standard .jpg or .png formats. ref: https://www.kaggle.com/datasets/samuelcortinhas/muffin-vs-chihuahua-image-classification/data