Update 12-05-2016: Currently, only yolo v1 (http://pjreddie.com/darknet/yolov1/) is supported. Yolo V2 (http://pjreddie.com/darknet/yolo/) is not supported. Batch norm layer is supported.
This is a caffe implementation of the YOLO:Real-Time Object Detection
Note, the caffe models are not trained in caffe, but converted from darknet's (.weight) files (http://pjreddie.com/darknet/yolov1/).
The converter is consisted of four steps:
- create .prototxt files for caffe from .cfg file in darkent
- initialize the caffe network and weights from .prototxt file
- read the weights from pre-trained darknet's (.weight) file
- replace the initialized weights with the weights in pre-trained darkenet's (.weight) file
- run "create_yolo_prototxt.py" to create .prototxt files
- run "create_yolo_caffemodel.py" to create .caffemodel files
- run "yolo_main.py" to call yolo in caffe
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first, you need to download the pretrained yolo weight files (http://pjreddie.com/darknet/yolov1/) and .cfg files (https://github.com/pjreddie/darknet/tree/master/cfg/yolov1)
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run create_yolo_prototxt.py to create .prototxt files
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after that, run create_yolo_caffemodel.py to create the caffemodel from yolo's (.weight) files
- "python create_yolo_caffemodel.py -m train_val_prototxt.filename -w yoloweights_filename -o caffemodel_filename"
replace train_val_prototxt.filename with /your/path/to/yolo_train_val.prototxt (yolo_small, yolo_tiny), yoloweights_filename with /your/path/to/yolo.weights (yolo-small, yolo-tiny), and caffemodel_filename with your output caffemodel name,
e.g. "python create_yolo_caffemodel.py -m yolo_train_val.prototxt -w yolo.weights -o yolo.caffemodel"
run yolo_main.py to do yolo object detection for the input image
- "python yolo_main.py -m model_filename -w weight_filename -i image_filename"
replace model_filename with /your/path/to/yolo_small_deploy.prototxt or yolo_tiny_deploy.prototxt, weight_filename with /your/path/to/yolo_tiny.caffemodel or yolo_small.caffemodel and image_filename with the target image file
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Caffe, pycaffe
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Opencv2
According to the LICENSE file of the original code,
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Me and original author hold no liability for any damages
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Do not use this on commercial!