Day #281 - Yolo based Object Counting and Duplicate Removal

Today's learning is Yolo based object counting, duplicate removal using intersection over union metric.

	import cv2
	import sys
	import os
	#Windows 10 Setup
	from darkflow.net.build import TFNet
	sys.path.append(r"E:\Code_Repo\darkflow\darkflow")
	options = {
	'model': 'E:\\Code_Repo\\darkflow\\cfg\\yolo.cfg',
	'load': 'E:\\Code_Repo\\darkflow\\yolov2.weights',
	'threshold': 0.14,
	'gpu': 1.0
	}
	tfnet = TFNet(options)
	#https://github.com/tejaslodaya/car-detection-yolo/blob/master/app_utils.py
	def iou(box1, box2):
	"""Implement the intersection over union (IoU) between box1 and box2
	Arguments:
	box1 -- first box, list object with coordinates (x1, y1, x2, y2)
	box2 -- second box, list object with coordinates (x1, y1, x2, y2)
	"""
	# Calculate the (y1, x1, y2, x2) coordinates of the intersection of box1 and box2. Calculate its Area.
	xi1 = max(box1[0], box2[0])
	yi1 = max(box1[1], box2[1])
	xi2 = min(box1[2], box2[2])
	yi2 = min(box1[3], box2[3])
	inter_area = (yi2 - yi1) * (xi2 - xi1)
	# Calculate the Union area by using Formula: Union(A,B) = A + B - Inter(A,B)
	box1_area = (box1[2] - box1[0]) * (box1[3] - box1[1])
	box2_area = (box2[2] - box2[0]) * (box2[3] - box2[1])
	union_area = box1_area + box2_area - inter_area
	# compute the IoU
	iou = inter_area / union_area
	return iou
	def Object_Count_Yolo(imagefilepath):
	coordinates = []
	boxes = []
	boxlabels = []
	finalboxes = []
	finalboxlabels = []
	img = cv2.imread(imagefilepath, cv2.IMREAD_COLOR)
	result = tfnet.return_predict(img)
	for data in result:
	coordinates = [data['topleft']['x'], data['topleft']['y'],data['bottomright']['x'], data['bottomright']['y']]
	boxes.append(coordinates)
	boxlabels.append(data['label'])
	for k in range(0,len(boxes)):
	selectflag = 0
	for m in range(k+1,len(boxes)):
	iouvalue = iou(boxes[k],boxes[m])
	if iouvalue > .7:
	selectflag = 1
	if(selectflag==0):
	finalboxes.append(boxes[k])
	finalboxlabels.append(boxlabels[k])
	return len(finalboxes)
	def diffObjectCount(SourceImagepath, DestinationImagePath):
	#Compute and Find Difference in Count
	#Return %% based on Count Difference
	SourceObjectCount = Object_Count_Yolo(SourceImagepath)
	DestinationObjectCount = Object_Count_Yolo(DestinationImagePath)
	print(SourceObjectCount)
	print(DestinationObjectCount)

view raw Yolo_Based_Object_Counting.py hosted with ❤ by GitHub

Happy Learning!!!