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README.md
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@@ -42,8 +42,9 @@ SegmentationClass: Contains PNG images with annotations.
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ImageSets: Contains TXT records for data partitioning.
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## Data Collection and Processing
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The main goal is to combine all the files into three datasets (train, test, validation) with two columns of images. The first step is to write a csv file containing all the labels for all images.
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After that, according to the csv file, we split all the images into three folders of train, test, validation. Each folder contains two groups of files: pictureid_original.jpg, and pictureid_segmentation.jpg.
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I then upload the zip file of these three folders and read those files in the load_dataset function.
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ImageSets: Contains TXT records for data partitioning.
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## Data Collection and Processing
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+
The main goal is to combine all the files into three datasets (train, test, validation) with two columns of images. The first step is to write a csv file containing all the labels for all images.
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After that, according to the csv file, we split all the images into three folders of train, test, validation. Each folder contains two groups of files: pictureid_original.jpg, and pictureid_segmentation.jpg.
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All the data processing code is uploaded in the Project1_dataset.ipynb file.
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I then upload the zip file of these three folders and read those files in the load_dataset function.
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