push streame

image_identification/controllers/image.py

@@ -3,6 +3,7 @@ import io
 import json
 import os
 import pathlib
+import subprocess
 import time
 
 import aiohttp
@@ -58,10 +59,12 @@ async def analyze(image: UploadFile):
 
 @router.websocket("/analyze_video")
 async def analyze_video(websocket: WebSocket):
-    rtmp_url = "rtmp://localhost/live/livestream"
+    rtmp_url = "rtmp://192.168.0.136/live/livestream"
+    output_url = "rtmp://192.168.0.136/live/livestream_output"
     cap = cv2.VideoCapture(rtmp_url)
     frame_number = 0
     frame_rate = 30
+    fps = int(cap.get(cv2.CAP_PROP_FPS))
 
     await websocket.accept()
     fourcc = cv2.VideoWriter.fourcc("M", "P", "4", "V")
@@ -70,8 +73,11 @@ async def analyze_video(websocket: WebSocket):
     print(cap.get(4))
     os.chdir("framers")
     video = None
+    ffmpeg_command = None
+    ffmpeg_process = None
     try:
         while True:
+            start = time.perf_counter()
             ret, frame = cap.read()
             if not ret:
                 print("无法读取视频帧")
@@ -85,20 +91,56 @@ async def analyze_video(websocket: WebSocket):
                 result = model_instance.predict(frame)
                 vis_im = fd.vision.vis_detection(frame, result, score_threshold=0.5)
                 # cv2.imwrite(frame_filename, vis_im)
+                width = vis_im.shape[1]
+                height = vis_im.shape[0]
                 if video is None:
                     video = cv2.VideoWriter(
                         "__output__.mp4",
                         fourcc,
                         30.0,
-                        (vis_im.shape[1], vis_im.shape[0]),
+                        (width, height),
                     )
+                if ffmpeg_command is None:
+                    # 创建ffmpeg进程以推送视频流
+                    ffmpeg_cmd = [
+                        "ffmpeg",
+                        "-y",
+                        "-f",
+                        "rawvideo",
+                        "-vcodec",
+                        "rawvideo",
+                        "-s",
+                        f"{width}x{height}",
+                        "-pix_fmt",
+                        "bgr24",
+                        "-r",
+                        str(fps),
+                        "-i",
+                        "-",
+                        "-c:v",
+                        "libx264",
+                        "-pix_fmt",
+                        "yuv420p",
+                        "-preset",
+                        "ultrafast",
+                        "-f",
+                        "flv",
+                        output_url,
+                    ]
+                if ffmpeg_process is None:
+                    ffmpeg_process = subprocess.Popen(ffmpeg_cmd, stdin=subprocess.PIPE)
+                ffmpeg_process.stdin.write(vis_im.tobytes())
                 video.write(vis_im)
-                print(vis_im.shape)
+                print(f"第{frame_number}帧")
+                print(result)
                 await websocket.send_text(fd.vision.fd_result_to_json(result=result))
                 # await websocket.send_text(frame_filename)
             else:
                 print(frame.shape)
                 video.write(frame)
+            end = time.perf_counter()
+            cost = end - start
+            print(f"time spend {cost}")
             frame_number += 1
     except WebSocketDisconnect:
         print("close")

image_identification/model/model.py

@@ -4,8 +4,8 @@ import fastdeploy as fd
 
 # Configurations
 model_dir = "yolov5s_infer"
-device = "gpu"
+device = "cpu"
-use_trt = True
+use_trt = False
 
 # Prepare model
 model_file = os.path.join(model_dir, "model.pdmodel")

poetry.lock

@@ -420,13 +420,13 @@ url = "https://pypi.tuna.tsinghua.edu.cn/simple"
 reference = "mirrors"
 
 [[package]]
-name = "fastdeploy-gpu-python"
+name = "fastdeploy-python"
 version = "1.0.7"
 description = "Deploy Kit Tool For Deeplearning models."
 optional = false
 python-versions = "*"
 files = [
-    {file = "fastdeploy_gpu_python-1.0.7-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:f92e9414e69b56b092d1327118912e8c5fa0acc32a0d9f4e971145e888f8d72d"},
+    {file = "fastdeploy_python-1.0.7-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:6f1b9c6eeefed4b63b9ba28335d857d6dd4fd9b6e9090a6e9688c60b553a4c42"},
 ]
 
 [package.dependencies]
@@ -444,7 +444,7 @@ mypy = ["mypy (==0.600)"]
 
 [package.source]
 type = "url"
-url = "https://bj.bcebos.com/fastdeploy/release/wheels/fastdeploy_gpu_python-1.0.7-cp310-cp310-manylinux1_x86_64.whl"
+url = "https://bj.bcebos.com/fastdeploy/release/wheels/fastdeploy_python-1.0.7-cp39-cp39-macosx_10_14_x86_64.whl"
 
 [[package]]
 name = "fastdeploy-tools"
@@ -737,13 +737,13 @@ reference = "mirrors"
 
 [[package]]
 name = "pydantic"
-version = "2.4.1"
+version = "2.4.2"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "pydantic-2.4.1-py3-none-any.whl", hash = "sha256:2b2240c8d54bb8f84b88e061fac1bdfa1761c2859c367f9d3afe0ec2966deddc"},
+    {file = "pydantic-2.4.2-py3-none-any.whl", hash = "sha256:bc3ddf669d234f4220e6e1c4d96b061abe0998185a8d7855c0126782b7abc8c1"},
-    {file = "pydantic-2.4.1.tar.gz", hash = "sha256:b172505886028e4356868d617d2d1a776d7af1625d1313450fd51bdd19d9d61f"},
+    {file = "pydantic-2.4.2.tar.gz", hash = "sha256:94f336138093a5d7f426aac732dcfe7ab4eb4da243c88f891d65deb4a2556ee7"},
 ]
 
 [package.dependencies]
@@ -1336,4 +1336,4 @@ reference = "mirrors"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.13"
-content-hash = "f1ddca71df771166e502ffab7d603041816df3290b39513a7e5bacf7cb343f8a"
+content-hash = "b1d0db5e3e467c63b7794237b977baadd64738b17490597f63dba35ded184000"

pyproject.toml

@@ -7,7 +7,8 @@ readme = "README.md"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.13"
-fastdeploy-gpu-python = { url = "https://bj.bcebos.com/fastdeploy/release/wheels/fastdeploy_gpu_python-1.0.7-cp310-cp310-manylinux1_x86_64.whl" }
+# fastdeploy-gpu-python = { url = "https://bj.bcebos.com/fastdeploy/release/wheels/fastdeploy_gpu_python-1.0.7-cp310-cp310-manylinux1_x86_64.whl" }
+fastdeploy-python = { url = "https://bj.bcebos.com/fastdeploy/release/wheels/fastdeploy_python-1.0.7-cp39-cp39-macosx_10_14_x86_64.whl" }
 numpy = "^1.26.0"
 opencv-python = "^4.8.0.76"
 python-multipart = "^0.0.6"