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--- |
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license: mit |
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task_categories: |
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- text-classification |
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- text-generation |
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language: |
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- en |
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tags: |
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- code |
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pretty_name: '*' |
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size_categories: |
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- 0.001M<n<0.0011M |
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--- |
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# Modified Coco Dataset Files |
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# Required dependencies |
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``` |
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OpenCV (cv2): |
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pip install opencv-python |
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``` |
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# img_data.psv |
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Extract of the coco dataset containing the following labels: ```["airplane", "backpack", "cell phone", "handbag", "suitcase", "knife", "laptop", "car"]``` |
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``` |
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Structured as follows: |
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| Field | Description | |
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| --------------- | --------------------------------------------------------------------------------------------------- | |
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| file_name | Name of image file (.png) | |
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| height | Image height prior to padding | |
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| width | Image width prior to padding | |
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| annotations | Array of boundary box array, label pairs. Bbox arrays are of the form [x_min, y_min, width, height] | |
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1.09k rows |
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``` |
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# /data (folder) |
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This directory contains a selection of zero-padded COCO images that correspond to img_data.parquet. |
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# display_boundary.py |
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Mini gui for viewing images with their boundary boxes, don't need to pay attention to how it works, just do the following: |
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Ensure you're in the same working directory as display_boundary.py |
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``` |
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cd mini_coco_dataset |
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``` |
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``` |
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python display_boundary.py |
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``` |
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- It takes an image name as input (x.png), to find image names look in the data folder. |
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If you have any questions or issues, feel free to keep them to yourself. |
