70 lines
No EOL
2.6 KiB
Python
70 lines
No EOL
2.6 KiB
Python
# source from https://dipankarmedh1.medium.com/real-time-object-detection-with-yolo-and-webcam-enhancing-your-computer-vision-skills-861b97c78993
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from ultralytics import YOLO
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import cv2
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import math
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# model
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# model = YOLO("yolov8x.pt")
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model = YOLO('yolov8n_full_integer_quant_edgetpu.tflite', task="detect") # Load an official Detect model
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# start webcam
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cap = cv2.VideoCapture(0)
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cap.set(3, 640)
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cap.set(4, 640)
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# object classes
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classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",
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"traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",
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"dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",
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"handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",
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"baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",
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"fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",
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"carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",
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"diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",
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"microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",
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"teddy bear", "hair drier", "toothbrush"
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]
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while True:
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success, img = cap.read()
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# img = cv2.resize(img, (512, 512), cv2.INTER_AREA)
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print(f"Image dimensions: {img.shape}")
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results = model.track(img, persist=True, stream=True)
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# coordinates
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for r in results:
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boxes = r.boxes
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for box in boxes:
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# bounding box
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x1, y1, x2, y2 = box.xyxy[0]
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x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) # convert to int values
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# put box in cam
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cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
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# confidence
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confidence = math.ceil((box.conf[0]*100))/100
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print("Confidence --->",confidence)
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# class name
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cls = int(box.cls[0])
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print("Class name -->", classNames[cls])
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# object details
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org = [x1, y1]
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font = cv2.FONT_HERSHEY_SIMPLEX
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fontScale = 1
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color = (255, 0, 0)
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thickness = 2
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cv2.putText(img, classNames[cls], org, font, fontScale, color, thickness)
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cv2.imshow('Webcam', img)
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if cv2.waitKey(1) == ord('q'):
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break
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cap.release()
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cv2.destroyAllWindows() |