save video detection result as file

.vscode/settings.json

@@ -0,0 +1,20 @@
+{
+    "MicroPython.executeButton": [
+        {
+            "text": "▶",
+            "tooltip": "运行",
+            "alignment": "left",
+            "command": "extension.executeFile",
+            "priority": 3.5
+        }
+    ],
+    "MicroPython.syncButton": [
+        {
+            "text": "$(sync)",
+            "tooltip": "同步",
+            "alignment": "left",
+            "command": "extension.execute",
+            "priority": 4
+        }
+    ]
+}

README.md

@@ -30,7 +30,9 @@
 ## 先把下面这些库装好,python不是3.8版本的话会有奇妙的bug
 **The dependency onnxruntime might be hard to be installed on Linux platforms.**
 
-**Linux装onnxruntime是真的坐牢，慎用**
+**Please install onnxruntime in conda virtual env.**
+
+**Linux装onnxruntime是真的坐牢，慎用，或者转用conda环境装**
 * Python(3.8 for recommended version) and pip
 * opencv-python
 * numpy==1.23.0
@@ -86,6 +88,9 @@
 * Check the detect result through the new window created by opencv
 * 通过opencv打开的视频流窗口查看推理结果
 
+* The detect result will be saved in resultsave/video folder.
+* 推理结果会被保留在resultsave/video目录下
+
 * Click "q" to end the detect process.
 * 按“q”键终止推理进程
 
@@ -113,13 +118,16 @@
 * Check the detect result through the new window created by opencv
 * 通过opencv打开的视频流窗口查看推理结果
 
+* The detect result will be saved in resultsave/video folder.
+* 推理结果会被保留在resultsave/video目录下
+
 * Click "q" to end the detect process.
 * 按“q”键终止推理进程
 
 # Todo待完成
 
-* Save the VideoStream detection result as a file
-* 以文件形式保存视频流推理结果
+* Save the VideoStream detection result as a file ✔ (done!)
+* 以文件形式保存视频流推理结果 ✔（已完成！）
 * Write an UI to adapt most usage
 * 写一个能适用于大多数场景需求的UI
 * Multi CPU core Inferences

detect.py

@@ -259,13 +259,31 @@ def run(img):
             assert os.path.exists(opt.videofile), "视频文件不存在"
             cap = cv2.VideoCapture(opt.videofile)  # 用opencv打开视频文件，转换为视频流
             print("Opened VideoStream.")
+            print(f"Video width:{int(cap.get(3))} Video height:{int(cap.get(4))}")
+            # 查看结果文件夹最后的视频序号并生成此次结果视频文件
+            folderChecker = os.listdir("resultsave/video/")
+            if len(folderChecker) == 0:
+                savePath = f"resultsave/video/0.mp4"
+            else:
+                savePath = f"resultsave/video/{int(sorted(folderChecker, reverse=True)[0].split(".")[0])+1}.mp4"
+            # 帧率调整
+            fps = 25.0
+            # 创建结果视频写入器以保存文件
+            vw = cv2.VideoWriter(
+                savePath,
+                cv2.VideoWriter.fourcc(*"mp4v"),
+                fps,
+                (int(cap.get(3)), int(cap.get(4))),
+            )
             while cap.isOpened():
                 # 按下q键退出推理
                 if cv2.waitKey(1) & 0xFF == ord("q"):
+                    vw.release()
                     break
                 ret, img = cap.read()  # 获取视频的开启状态和每一帧图片
                 if ret:
                     run(img)
+                    vw.write(resframe)
                     cv2.imshow("Videostream", resframe)
                 else:
                     cv2.waitKey(1)  # 防止推理速度不够快，有空白帧
@@ -280,18 +298,38 @@ def run(img):
         # 摄像头实时流源
         cap = cv2.VideoCapture(opt.source)  # 用opencv打开摄像头，0为默认摄像头
         print("Opened Camera.")
+        print(f"Video width:{int(cap.get(3))} Video height:{int(cap.get(4))}")
+        # 查看结果文件夹最后的视频序号并生成此次结果视频文件
+        folderChecker = os.listdir("resultsave/video/")
+        if len(folderChecker) == 0:
+            savePath = f"resultsave/video/0.mp4"
+        else:
+            savePath = f"resultsave/video/{int(sorted(folderChecker, reverse=True)[0].split(".")[0])+1}.mp4"
+        # 帧率调整
+        fps = 25.0
+        # 创建结果视频写入器以保存文件
+        vw = cv2.VideoWriter(
+            savePath,
+            cv2.VideoWriter.fourcc(*"mp4v"),
+            fps,
+            (int(cap.get(3)), int(cap.get(4))),
+        )
         while True:
             # 按下q键退出推理
             if cv2.waitKey(1) & 0xFF == ord("q"):
+                vw.release()
                 break
             ret, img = cap.read()  # 获取视频的开启状态和每一帧图片
             if ret:
                 run(img)
+                vw.write(resframe)
                 cv2.imshow("CameraStream", resframe)
             else:
                 cv2.waitKey(1)  # 防止推理速度不够快，有空白帧
 
     if "cap" in globals():
         if cap.isOpened:
             cap.release()
+    if "vw" in globals():
+        vw.release()
     cv2.destroyAllWindows()