YOLO in caffe
__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.__
Introduction
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
Usage
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
Convert yolo's (.weight) files to caffemodel
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)
run create_yolo_prototxt.py to create .prototxt files
after that, run create_yolo_caffemodel.py to create the caffemodel from yolo's (.weight) files
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"
Main file usage
run yolo_main.py to do yolo object detection for the input image
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
Requirements
Copyrights
According to the LICENSE file of the original code,