本案例将演示通过在 PC 端上运行脚本程序,通过 StackFlow 的 API 接口获取 yolo 的检测数据,并启动预览窗口实时查看检测情况。
apt install llm-camera llm-yolo # SoftWare Package
apt install llm-model-yolo11n-npu1 llm-model-yolo11n-pose-npu1 llm-model-yolo11n-hand-pose-npu1 # Model Package
下载客户端测试脚本,确保 PC 与 LLM630 Compute Kit 处于同一网段下。PC 端需准备 Python 环境并通过 Pip 包管理器安装 opencv-python
和 tornado
依赖包。
pip install opencv-python tornado
pip install opencv-python tornado -i https://mirrors.aliyun.com/pypi/simple # For Chinese users
复制并保存下方脚本,并运行时候传入设备实际的 IP 地址参数。
python llm-yolo-visual.py --host 192.168.20.24
import argparse
import base64
import cv2
import json
import numpy as np
import select
import socket
import sys
import time
import threading
import tornado.ioloop
import tornado.web
import platform
if platform.system() == "Windows":
import msvcrt
latest_frame = [None]
COCO_KP_PAIRS = [
(0, 2), (2, 4), (0, 1), (1, 3),
(6, 5), (6, 8), (8, 10), (5, 7),
(7, 9), (12, 11), (6, 12), (12, 14),
(14, 16), (5, 11), (11, 13), (13, 15)
]
COCO_COLORS = [
(255,0,0), (0,255,0), (0,0,255), (255,255,0),
(255,0,255), (0,255,255), (128,128,0), (128,0,128)
]
HAND_KP_PAIRS = [
(0, 1), (1, 2), (2, 3), (3, 4),
(0, 5), (5, 6), (6, 7), (7, 8),
(0, 17), (17, 18), (18, 19), (19, 20),
(5, 9), (9, 13), (13, 17),
(9, 10), (10, 11), (11, 12),
(13, 14), (14, 15), (15, 16)
]
HAND_COLORS = [
(255,0,0), (0,255,0), (0,0,255), (255,255,0),
(255,0,255), (0,255,255), (128,128,0), (128,0,128),
(0,128,128), (64,64,255), (255,64,64), (64,255,64)
]
class MJPEGHandler(tornado.web.RequestHandler):
def get(self):
self.set_header('Content-type', 'multipart/x-mixed-replace; boundary=frame')
while True:
if latest_frame[0] is not None:
ret, jpeg = cv2.imencode('.jpg', latest_frame[0])
if ret:
self.write(b'--frame\r\n')
self.write(b'Content-Type: image/jpeg\r\n\r\n')
self.write(jpeg.tobytes())
self.write(b'\r\n')
self.flush()
tornado.ioloop.IOLoop.current().add_callback(lambda: None) # yield to event loop
def start_webstream():
app = tornado.web.Application([
(r"/video_feed", MJPEGHandler),
])
app.listen(5000)
print("Tornado webstream started at http://localhost:5000/video_feed")
tornado.ioloop.IOLoop.current().start()
def create_tcp_connection(host, port):
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.connect((host, port))
return sock
def send_json(sock, data):
json_data = json.dumps(data, ensure_ascii=False) + '\n'
sock.sendall(json_data.encode('utf-8'))
recv_buffer = ""
def receive_response(sock):
global recv_buffer
while '\n' not in recv_buffer:
part = sock.recv(4096).decode('utf-8')
if not part:
break
recv_buffer += part
if '\n' in recv_buffer:
line, recv_buffer = recv_buffer.split('\n', 1)
return line.strip()
else:
line, recv_buffer = recv_buffer, ""
return line.strip()
def close_connection(sock):
if sock:
sock.close()
def create_init_data(response_format, deivce, enoutput, frame_height, frame_width, enable_webstream, rtsp):
return {
"request_id": "camera_001",
"work_id": "camera",
"action": "setup",
"object": "camera.setup",
"data": {
"response_format": "image.yuvraw.base64" if response_format =="yuv" else "image.jpeg.base64",
"input": deivce,
"enoutput": enoutput,
"frame_width": frame_width,
"frame_height": frame_height,
"enable_webstream": enable_webstream,
"rtsp": "rtsp.1280x720.h265" if rtsp == "h265" else "rtsp.1280x720.h264",
}
}
def parse_setup_response(response_data):
error = response_data.get('error')
if error and error.get('code') != 0:
print(f"Error Code: {error['code']}, Message: {error['message']}")
return None
return response_data.get('work_id')
def reset(sock):
sent_request_id = 'reset_000'
reset_data = {
"request_id": sent_request_id,
"work_id": "sys",
"action": "reset"
}
ping_data = {
"request_id": "ping_000",
"work_id": "sys",
"action": "ping"
}
send_json(sock, reset_data)
while True:
try:
send_json(sock, ping_data)
time.sleep(1)
except (BrokenPipeError, ConnectionResetError, OSError) as e:
return # Sock disconnection indicates reset is complete
def setup(sock, init_data):
sent_request_id = init_data['request_id']
send_json(sock, init_data)
while True:
response = receive_response(sock)
response_data = json.loads(response)
if response_data.get('request_id') == sent_request_id:
return parse_setup_response(response_data)
def exit_session(sock, deinit_data):
send_json(sock, deinit_data)
print("Exit")
def parse_inference_response(response_data):
error = response_data.get('error')
if error and error.get('code') != 0:
print(f"Error Code: {error['code']}, Message: {error['message']}")
return None
return {
"work_id": response_data.get("work_id"),
"object": response_data.get("object"),
"data": response_data.get("data")
}
def parse_yolo_result(data):
results = []
for item in data:
bbox = [float(x) for x in item.get('bbox', [])]
kps = [float(x) for x in item.get('kps', [])]
cls = item.get('class', '')
conf = float(item.get('confidence', 0))
results.append({
'bbox': bbox,
'class': cls,
'confidence': conf,
'kps': kps
})
return results
def draw_keypoints(frame, kps, num_points, colors):
for i in range(num_points):
x, y, s = int(kps[i*3]), int(kps[i*3+1]), kps[i*3+2]
if s > 0.05:
cv2.circle(frame, (x, y), 3, colors[i % len(colors)], -1)
def draw_lines(frame, kps, pairs, colors):
for idx, (i, j) in enumerate(pairs):
xi, yi, si = int(kps[i*3]), int(kps[i*3+1]), kps[i*3+2]
xj, yj, sj = int(kps[j*3]), int(kps[j*3+1]), kps[j*3+2]
if si > 0.05 and sj > 0.05:
cv2.line(frame, (xi, yi), (xj, yj), colors[idx % len(colors)], 2)
def main(args):
sock = create_tcp_connection(args.host, args.port)
frame_height, frame_width = args.imgsz
try:
print("Reset...")
reset(sock)
close_connection(sock)
sock = create_tcp_connection(args.host, args.port)
print("Setup Camera...")
init_data = create_init_data(
response_format = args.format,
enoutput=args.enoutput,
deivce=args.device,
frame_height=frame_height,
frame_width=frame_width,
enable_webstream=args.webstream,
rtsp=args.rtsp
)
camera_work_id = setup(sock, init_data)
if camera_work_id is not None:
print(f"Camera setup with work_id: {camera_work_id}")
else:
print("Camera setup failed.")
return
print("Setup Yolo...")
yolo_init_data = {
"request_id": "yolo_001",
"work_id": "yolo",
"action": "setup",
"object": "yolo.setup",
"data": {
"model": args.model,
"response_format": "yolo.box",
"input": camera_work_id,
"enoutput": True,
}
}
yolo_work_id = setup(sock, yolo_init_data)
if yolo_work_id is not None:
print(f"Yolo setup with work_id: {yolo_work_id}")
else:
print("Yolo setup failed.")
return
yolo_results = []
webstream_thread = None
if args.webstream:
webstream_thread = threading.Thread(target=start_webstream, daemon=True)
webstream_thread.start()
while True:
if platform.system() == "Windows":
if msvcrt.kbhit():
key = msvcrt.getwch()
if key == 'q':
print("Quit by user.")
break
else:
if sys.stdin in select.select([sys.stdin], [], [], 0)[0]:
key = sys.stdin.readline().strip()
if key == 'q':
print("Quit by user.")
break
response = receive_response(sock)
if not response:
continue
response_data = json.loads(response)
Rawdata = parse_inference_response(response_data)
if Rawdata is None:
break
work_id = Rawdata.get("work_id")
object = Rawdata.get("object")
data = Rawdata.get("data")
if work_id == yolo_work_id and object == "yolo.box":
yolo_results = parse_yolo_result(data)
elif work_id == camera_work_id and object in ["image.jpeg.base64", "image.yuyv422.base64"]:
decoded = base64.b64decode(data)
if object == "image.yuyv422.base64" or args.format == "yuv":
yuv_frame = np.frombuffer(decoded, dtype=np.uint8).reshape((frame_height, frame_width, 2))
bgr_frame = cv2.cvtColor(yuv_frame, cv2.COLOR_YUV2BGR_YUY2)
else:
jpg_array = np.frombuffer(decoded, dtype=np.uint8)
bgr_frame = cv2.imdecode(jpg_array, cv2.IMREAD_COLOR)
if bgr_frame is not None:
if yolo_results:
for det in yolo_results:
x1, y1, x2, y2 = map(int, det['bbox'])
cls = det['class']
conf = det['confidence']
cv2.rectangle(bgr_frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
cv2.putText(
bgr_frame, f"{cls} {conf:.2f}", (x1, y1 - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2
)
kps = det.get('kps', [])
if not kps:
continue
if args.model == "yolo11n-pose-npu1" and len(kps) == 17 * 3:
draw_keypoints(bgr_frame, kps, 17, COCO_COLORS)
draw_lines(bgr_frame, kps, COCO_KP_PAIRS, COCO_COLORS)
elif args.model == "yolo11n-hand-pose-npu1" and len(kps) == 21 * 3:
draw_keypoints(bgr_frame, kps, 21, HAND_COLORS)
draw_lines(bgr_frame, kps, HAND_KP_PAIRS, HAND_COLORS)
if args.webstream:
latest_frame[0] = bgr_frame.copy()
if args.host not in ["localhost", "127.0.0.1"]:
cv2.imshow("YOLO Detection", bgr_frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
exit_session(sock, {
"request_id": "yolo_exit",
"work_id": yolo_work_id,
"action": "exit"
})
exit_session(sock, {
"request_id": "camera_exit",
"work_id": camera_work_id,
"action": "exit"
})
time.sleep(3) # Allow time for the exit command to be processed
finally:
close_connection(sock)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="TCP Client to send JSON data.")
parser.add_argument("--host", type=str, default="localhost", help="Server hostname (default: localhost)")
parser.add_argument("--port", type=int, default=10001, help="Server port (default: 10001)")
parser.add_argument("--device", type=str, default="axera_single_sc850sl", help="Camera name, i.e. axera_single_sc850sl or /dev/video0")
parser.add_argument("--enoutput", type=bool, default=True, help="Whether to output image data")
parser.add_argument("--format", "--output-format", type=str, default="jpeg", help="Output image data format, i.e. jpeg or yuv")
parser.add_argument("--imgsz", "--img", "--img-size", nargs="+", type=int, default=[320, 320], help="image (h, w)")
parser.add_argument("--webstream", action="store_true", help="Enable webstream")
parser.add_argument("--rtsp", default="h264", help="rtsp output, i.e. h264 or h265")
parser.add_argument("--model", type=str, default="yolo11n-npu1", help="Model name, i.e. yolo11n-npu1 or yolo11n-pose-npu1, yolo11n-hand-pose-npu1")
args = parser.parse_args()
main(args)
电脑屏幕将显示摄像头画面和检测结果,如下图所示。按下键盘按键 “q” 可退出。