92 lines
No EOL
3.9 KiB
Python
92 lines
No EOL
3.9 KiB
Python
import websockets
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import asyncio
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import numpy as np
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from ultralytics import YOLO
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import cv2
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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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model = YOLO('yolov8m.pt') # Load an official Detect model
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async def handle_connection(websocket, path):
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print(f"Connection from: {path}")
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try:
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while True:
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raw_data = await websocket.recv()
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print(f"downloaded bytes: {len(raw_data)}")
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# nparr = np.frombuffer(decoded_bytes, np.uint8).reshape((480, 640, 3))
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nparr = np.frombuffer(raw_data, dtype=np.uint8)
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frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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# frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
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cv2.imshow("from_remote", frame)
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# Perform object detection
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results = model.track(frame, persist=True)
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for r in results:
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lines = ""
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boxes = r.boxes
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for box in boxes:
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if box.cls[0].item() == 0 and not box.id is None:
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# bounding box
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id = box.id.int().cpu().tolist()
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# x1, y1, x2, y2 = box.xyxy[0]
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# # 2.08333 = 1/480 * 1000 or normalize, then save 4 sig-figures and cast to int
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# # 1.5625 = 1/640 * 1000 or normalize, then save 4 sig-figures and cast to int
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# x1, x2, y1, y2 = int(x1), int(x2), int(y1), int(y2)
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# # put box in cam
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# cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 255), 3)
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# # class name
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# cls = int(box.cls[0])
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# # object details
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# org = [x1, y1]
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# org2 = [x1, y1+50]
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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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# color_w = (255, 255, 255)
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# thickness = 2
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# cv2.putText(frame, classNames[cls], org, font, fontScale, color, thickness)
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# cv2.putText(frame, str(id), org2, font, fontScale, color_w, thickness)
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x1, y1, x2, y2 = box.xyxyn[0]
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x1, y1, x2, y2 = int(x1 * 1000), int(y1 * 1000), int(x2 * 1000), int(y2 * 1000)
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lines += f"{id} {x1}:{y1} {x2}:{y2}\n"
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# cv2.imshow('Webcam', frame)
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# if cv2.waitKey(1) == ord('q'):
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# break
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ret = lines.encode('utf-8')
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cv2.waitKey(1)
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await websocket.send(ret)
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except websockets.exceptions.ConnectionClosed:
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print(f"Client disconnected: {path}")
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if __name__ == "__main__":
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start_server = websockets.serve(handle_connection, "0.0.0.0", 6543)
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asyncio.get_event_loop().run_until_complete(start_server)
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asyncio.get_event_loop().run_forever() |