SPARK - Smart Parking Solution

import cv2
import numpy as np 
import argparse
import time

def load_yolo():
	net = cv2.dnn.readNet("yolov3.weights", "yolov3.cfg")
	classes = []
	with open("coco.names", "r") as f:
		classes = [line.strip() for line in f.readlines()] 
	
	output_layers = [layer_name for layer_name in net.getUnconnectedOutLayersNames()]
	colors = np.random.uniform(0, 255, size=(len(classes), 3))
	return net, classes, colors, output_layers

def detect_objects(img, net, outputLayers):			
	blob = cv2.dnn.blobFromImage(img, scalefactor=0.00392, size=(416, 416), mean=(0, 0, 0), swapRB=True, crop=False)
	net.setInput(blob)
	outputs = net.forward(outputLayers)
	return blob, outputs

def get_box_dimensions(outputs, height, width):
	boxes = []
	confs = []
	class_ids = []
	for output in outputs:
		for detect in output:
			scores = detect[5:]
			#print(scores)
			class_id = np.argmax(scores)
			conf = scores[class_id]
			if conf > 0.5:
				center_x = int(detect[0] * width)
				center_y = int(detect[1] * height)
				w = int(detect[2] * width)
				h = int(detect[3] * height)
				x = int(center_x - w/2)
				y = int(center_y - h / 2)
				boxes.append([x, y, w, h])
				confs.append(float(conf))
				class_ids.append(class_id)
	return boxes, confs, class_ids

def draw_labels(boxes, confs, colors, class_ids, classes, img): 
	indexes = cv2.dnn.NMSBoxes(boxes, confs, 0.5, 0.4)
	font = cv2.FONT_HERSHEY_PLAIN
	status="vacant"
	poslist=[(800, 400)]
	spacecounter=3
	box=[]
	for i in range(len(boxes)):
		if i in indexes:
			x, y, w, h = boxes[i]
			label = str(classes[class_ids[i]])
			x1=np.arange(x,x+w)
			y1=np.arange(y,w+h)
			for i in range(len(x1)):
				for j in range(len(y1)):     
					box.append((x1[i],y1[j]))
			for i in poslist:
				if i in box:
					status='occupied'
					spacecounter=4
				else:
					status=status
                #color = colors[i]
			color = (255,0,0)
			if status=="occupied":
				color = (0,255,0)
			else:
				color = (0,0,255)
			cv2.rectangle(img, (x,y), (x+w, y+h), color, 2)
			cv2.putText(img, label, (x, y - 5), font, 2, color, 2)
	cv2.imshow("Image", img)
	return img, status, indexes, spacecounter

def start_video(video_path):
	model, classes, colors, output_layers = load_yolo()
	cap = cv2.VideoCapture(video_path)
	videoFps = cap.get(cv2.CAP_PROP_FPS)
# 	print(videoFps)
	result = cv2.VideoWriter('output1.avi',cv2.VideoWriter_fourcc('M','J','P','G'), videoFps, (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))))
	while True:
# 		cap.set(cv2.CAP_PROP_FPS,10) 
		_, frame = cap.read()
# 		frame=cv2.resize(frame,((1200,600)))
		height, width, channels = frame.shape
# 		print(frame.shape)
		blob, outputs = detect_objects(frame, model, output_layers)
		boxes, confs, class_ids = get_box_dimensions(outputs, height, width)
		finalImg, status, indexes, spacecounter = draw_labels(boxes, confs, colors, class_ids, classes, frame)
		cv2.putText(finalImg, status, (800, 450), cv2.FONT_HERSHEY_PLAIN, 2, (0,255,0), 2)
		cv2.putText(finalImg, "vacant", (450, 450), cv2.FONT_HERSHEY_PLAIN, 2, (0,255,0), 2)
		cv2.putText(finalImg, "vacant", (1150, 450), cv2.FONT_HERSHEY_PLAIN, 2, (0,255,0), 2)
		cv2.putText(finalImg, "vacant", (200, 450), cv2.FONT_HERSHEY_PLAIN, 2, (0,255,0), 2)
		cv2.putText(finalImg, "vacant", (1500, 450), cv2.FONT_HERSHEY_PLAIN, 2, (0,255,0), 2)
		cv2.putText(finalImg,f'Available parking:{spacecounter}/{3}',(100,100),cv2.FONT_HERSHEY_PLAIN,2,(0,255,0),2)
# 		print(spacecounter)
		result.write(finalImg)
# 		print(boxes)
		cv2.imshow("Image", finalImg)
		if cv2.waitKey(1) & 0xFF == ord('y'):
			break
	cap.release()
	result.release()
	cv2.destroyAllWindows()

start_video("istockphoto-1144667192-640_adpp_is.mp4")