Day #290 - Yolo from OpenCV DNN - Windows 10

OpenCV has examples to invoke Deep Network using readNet modules

Key Methods

• cv.dnn.readNet - Load the network
• cv.dnn.NMSBoxes - Non Max Suppression
• cv.dnn.blobFromImage - Input for Deep Network

Steps

	Package Install - pip install opencv-python
	Step #1 - git clone https://github.com/opencv/opencv
	Step #2 - Goto Path - opencv/opencv/tree/master/samples/dnn
	Link https://docs.opencv.org/master/da/d9d/tutorial_dnn_yolo.html
	Step #3 - Steps to Run
	example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392 --input=[PATH-TO-IMAGE-OR-VIDEO-FILE] --rgb
	Step #4 - cd E:\Code_Repo\opencv\samples\dnn
	Step #5 - For Image
	python object_detection.py --config="E:\\Code_Repo\\darkflow\\cfg\\yolo.cfg" --model="E:\\Code_Repo\\darkflow\\yolov2.weights" --classes="E:\\Code_Repo\\darkflow\\cfg\\coco.names" --width=416 --height=416 --scale=0.00392 --input="E:\Car_Detection\Data1\\frame214000.jpg" --rgb
	Step #6 - For Video
	python object_detection.py --config="E:\\Code_Repo\\darkflow\\cfg\\yolo.cfg" --model="E:\\Code_Repo\\darkflow\\yolov2.weights" --classes="E:\\Code_Repo\\darkflow\\cfg\\coco.names" --width=416 --height=416 --scale=0.00392 --input="E:\Car_Detection\\ch10_20190304115220.mp4" --rgb
	Another Good Ref - https://github.com/rdeepc/ExploreOpencvDnn

view raw yolo_from_opencv.txt hosted with ❤ by GitHub

Results

Happy Learning!!!