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Yolov3-custom-pedestrian-detection License: GPL v3 Python Version

📝 Table of Contents

PennFudanAugmentation

Darknet yolo: https://pjreddie.com/darknet/yolo/
Dataset: https://www.cis.upenn.edu/~jshi/ped_html/
The data set contains only 170 samples, so we expand the dataset by scaling or cropping each image.
1)genImageBoxLabel: Convert the original annotation to yolov3 label format.
2)splitImageDataset: Split images and labels file to train and test set.
3)testLabel: Rectangle image from yolov3 labels format to validate the labels data.
4)main: Main function to argument the image set by scaling and cropping method.


Dataset description before augmentation(170 sample images).


Dataset description after augmentation(5270 sample images).

trainPennFudan

Darknet config files for training.

DetectionEffect