tw-yshuang/coco2yolo

A CLI tool can create a specific task-dataset you want based on COCO dataset. Given the annotation JSON file, this tool will help you download the data and set the symbolic links from data_dir to task_dir !!

Hi 👋, I'm Y. S. Huang

A passionate machine vision developer from Taiwan

Every Choice🕹 will generate another Option🔠, so keep Fighting🦾 & Enjoy😎.

• 🔭 I’m currently working on Video-synopsis.
• 🌱 I’m currently learning Deep-Learning, Machine-Vision

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coco2yolo's Issues

Support for MS COCO format.

I have dataset in MS COCO format it has segmentation field also I want to include them in annotation files, but segmentation points are not included in the annotation files!

class 對應的 index 錯誤

Enter the categories name you wish(split: ', '): person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, hair drier, toothbrush
['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush']
The total number of the data: 4925
Index Correspond Table:
{'person': 0, 'bicycle': 1, 'car': 51, 'motorcycle': 3, 'airplane': 4, 'bus': 5, 'train': 6, 'truck': 7, 'boat': 8, 'traffic light': 9, 'fire hydrant': 10, 'stop sign': 11, 'parking meter': 12, 'bench': 13, 'bird': 14, 'cat': 15, 'dog': 52, 'horse': 17, 'sheep': 18, 'cow': 19, 'elephant': 20, 'bear': 77, 'zebra': 22, 'giraffe': 23, 'backpack': 24, 'umbrella': 25, 'handbag': 26, 'tie': 27, 'suitcase': 28, 'frisbee': 29, 'skis': 30, 'snowboard': 31, 'sports ball': 32, 'kite': 33, 'baseball bat': 34, 'baseball glove': 35, 'skateboard': 36, 'surfboard': 37, 'tennis racket': 38, 'bottle': 39, 'wine glass': 40, 'cup': 41, 'fork': 42, 'knife': 43, 'spoon': 44, 'bowl': 45, 'banana': 46, 'apple': 47, 'sandwich': 48, 'orange': 49, 'broccoli': 50, 'carrot': 51, 'hot dog': 52, 'pizza': 53, 'donut': 54, 'cake': 55, 'chair': 56, 'couch': 57, 'potted plant': 58, 'bed': 59, 'dining table': 60, 'toilet': 61, 'tv': 62, 'laptop': 63, 'mouse': 64, 'remote': 65, 'keyboard': 66, 'cell phone': 67, 'microwave': 68, 'oven': 69, 'toaster': 70, 'sink': 71, 'refrigerator': 72, 'book': 73, 'clock': 74, 'vase': 75, 'scissors': 76, 'teddy bear': 77, 'hair drier': 78, 'toothbrush': 79}

car 跟 carrot 都對應 51
dog 跟 hot dog 都對應 52
bear 跟 teddy bear 都對應 77

support non-JPG images

Currently coco2yolo only functions with .jpg images. Ideally support a parameter that allows choosing another extension (PNG, GIF).

pypi package?

It would be nice if this was published as a pypi package so it can be trivially installed with dependencies via pip install coco2yolo.

Is instance segmentation support planned?

Is instance segmentation support planned?
YOLO5 now supports segmentation

Windows 10 issues

I get an error "ImportError: cannot import name 'mknod' from 'os' (C:\Program Files\Python39\lib\os.py)"
Brief research tells me mknod doesn't work on Windows.
Altough it's likely not the best solution, I fixed it by just deleting "mknod" from line 9 and commenting out line 62 in submodules/FileSearcher.py.

In Windows 10 you'll also need to run VS Code as Admin, maybe mention this in README?