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pickle_vision/jetson/rtsp_yolo_stream.py
Ruslan Bakiev 549fd1da9d Initial commit
2026-03-06 09:43:52 +07:00

134 lines
4.1 KiB
Python

#!/usr/bin/env python3
"""
RTSP stream with YOLOv8 ball detection using GStreamer pipeline.
"""
import cv2
import time
import sys
from ultralytics import YOLO
BALL_CLASS_ID = 32 # sports ball
WIDTH = 1280
HEIGHT = 720
FPS = 25
PORT = 8554
def main():
source = sys.argv[1] if len(sys.argv) > 1 else "/opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h264.mp4"
print("Loading YOLOv8n model...")
model = YOLO("yolov8n.pt")
try:
model.to("cuda")
print("Using CUDA")
except:
print("Using CPU")
print(f"Opening: {source}")
cap = cv2.VideoCapture(source)
if not cap.isOpened():
print("ERROR: Cannot open source")
return 1
# GStreamer RTSP output pipeline
gst_out = (
f"appsrc ! "
f"video/x-raw,format=BGR,width={WIDTH},height={HEIGHT},framerate={FPS}/1 ! "
f"queue ! videoconvert ! video/x-raw,format=I420 ! "
f"x264enc tune=zerolatency bitrate=2000 speed-preset=ultrafast key-int-max=30 ! "
f"video/x-h264,profile=baseline ! "
f"rtspclientsink location=rtsp://127.0.0.1:{PORT}/live"
)
# Try simple UDP multicast instead
gst_out_udp = (
f"appsrc ! "
f"video/x-raw,format=BGR,width={WIDTH},height={HEIGHT},framerate={FPS}/1 ! "
f"videoconvert ! video/x-raw,format=I420 ! "
f"x264enc tune=zerolatency bitrate=2000 speed-preset=ultrafast ! "
f"h264parse ! "
f"mpegtsmux ! "
f"udpsink host=224.1.1.1 port=5000 auto-multicast=true"
)
# Or just write to file for testing
gst_file = (
f"appsrc ! "
f"video/x-raw,format=BGR,width={WIDTH},height={HEIGHT},framerate={FPS}/1 ! "
f"videoconvert ! video/x-raw,format=I420 ! "
f"x264enc tune=zerolatency ! "
f"mp4mux ! "
f"filesink location=/tmp/output_detection.mp4"
)
print(f"\nStarting detection stream...")
print(f"Output: /tmp/output_detection.mp4")
print("Press Ctrl+C to stop\n")
out = cv2.VideoWriter(gst_file, cv2.CAP_GSTREAMER, 0, FPS, (WIDTH, HEIGHT), True)
if not out.isOpened():
print("GStreamer writer failed, using regular file output")
out = cv2.VideoWriter('/tmp/output_detection.mp4',
cv2.VideoWriter_fourcc(*'mp4v'), FPS, (WIDTH, HEIGHT))
frame_count = 0
start = time.time()
total_detections = 0
try:
while True:
ret, frame = cap.read()
if not ret:
cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
continue
frame = cv2.resize(frame, (WIDTH, HEIGHT))
# Detection
results = model(frame, verbose=False, classes=[BALL_CLASS_ID], conf=0.25)
for r in results:
for box in r.boxes:
x1, y1, x2, y2 = map(int, box.xyxy[0])
conf = float(box.conf[0])
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 3)
cv2.putText(frame, f"Ball {conf:.2f}", (x1, y1-10),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
total_detections += 1
# FPS overlay
frame_count += 1
elapsed = time.time() - start
fps = frame_count / elapsed
cv2.putText(frame, f"FPS: {fps:.1f}", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
out.write(frame)
if frame_count % 50 == 0:
print(f"Frame {frame_count}, FPS: {fps:.1f}, Detections: {total_detections}")
# Stop after 10 seconds for test
if elapsed > 10:
print("\n10 second test complete")
break
except KeyboardInterrupt:
print("\nStopping...")
finally:
elapsed = time.time() - start
print(f"\nProcessed {frame_count} frames in {elapsed:.1f}s")
print(f"Average FPS: {frame_count/elapsed:.1f}")
print(f"Total detections: {total_detections}")
print(f"Output saved to: /tmp/output_detection.mp4")
cap.release()
out.release()
return 0
if __name__ == "__main__":
sys.exit(main())