Merge pull request avinashkranjan#2895 from smty2018/cartrack

Car Tracking using YOLO and OpenCV

Author: avinashkranjan

Car Detection OpenCV/ReadMe.txt

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+Car Tracking using YOLO and OpenCV:
+
+This project demonstrates car tracking in videos using the YOLO (You Only Look Once) object detection model and the OpenCV library. The YOLO model is used to detect cars in each frame of a video stream, and bounding boxes are drawn around the detected cars to track their movement.
+
+- Download YOLOv3 weights: [yolov3.weights](https://pjreddie.com/media/files/yolov3.weights)
+- Download YOLOv3 configuration: [yolov3.cfg](https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg)
+- Download COCO names file: [coco.names](https://github.com/pjreddie/darknet/blob/master/data/coco.names)
+
+pip install opencv-python

Car Detection OpenCV/app.py

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+import cv2
+import numpy as np
+
+
+yolo_net = cv2.dnn.readNet('yolov3.weights', 'yolov3.cfg')
+
+
+class_names = []
+with open('coco.names', 'r') as f:
+    class_names = f.read().strip().split('\n')
+
+
+video_capture = cv2.VideoCapture('video_file.mp4')
+
+while video_capture.isOpened():
+    ret, frame = video_capture.read()
+    if not ret:
+        break
+
+    height, width, _ = frame.shape
+
+   
+    blob = cv2.dnn.blobFromImage(frame, 0.00392, (416, 416), (0, 0, 0), True, crop=False)
+    yolo_net.setInput(blob)
+
+    layer_names = yolo_net.getUnconnectedOutLayersNames()
+    outs = yolo_net.forward(layer_names)
+
+    for out in outs:
+        for detection in out:
+            scores = detection[5:]
+
+            class_id = np.argmax(scores)
+            confidence = scores[class_id]
+            if confidence > 0.5 and class_id == 2: 
+                center_x = int(detection[0] * width)
+
+                center_y = int(detection[1] * height)
+                bbox_width = int(detection[2] * width)
+
+                bbox_height = int(detection[3] * height)
+
+                x = int(center_x - bbox_width / 2)
+                y = int(center_y - bbox_height / 2)
+                cv2.rectangle(frame, (x, y), (x + bbox_width, y + bbox_height), (0, 255, 0), 2)
+
+                
+    resized_frame = cv2.resize(frame, (720, 480))
+
+    cv2.imshow('Car Tracking', frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+video_capture.release()
+cv2.destroyAllWindows()

Car Detection OpenCV/coco.names

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+person
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush