openv: use new pipieline

plugins/opencv/package.json

@@ -36,5 +36,5 @@
    "devDependencies": {
       "@scrypted/sdk": "file:../../sdk"
    },
-   "version": "0.0.70"
+   "version": "0.0.72"
 }

plugins/opencv/src/opencv/__init__.py

@@ -1,22 +1,21 @@
 from __future__ import annotations
-from time import sleep
-from detect import DetectionSession, DetectPlugin
+
 from typing import Any, List, Tuple
-import numpy as np
-import asyncio
+
 import cv2
 import imutils
-Gst = None
-try:
-    from gi.repository import Gst
-except:
-    pass
-from scrypted_sdk.types import ObjectDetectionModel, ObjectDetectionResult, ObjectsDetected, Setting, VideoFrame
-from PIL import Image
-
-class OpenCVDetectionSession(DetectionSession):
+import numpy as np
+
+from detect import DetectPlugin
+
+import scrypted_sdk
+from scrypted_sdk.types import (ObjectDetectionGeneratorSession,
+                                ObjectDetectionResult,
+                                ObjectsDetected, Setting, VideoFrame)
+
+
+class OpenCVDetectionSession:
     def __init__(self) -> None:
-        super().__init__()
         self.cap: cv2.VideoCapture = None
         self.previous_frame: Any = None
         self.curFrame = None
@@ -110,8 +109,7 @@ def parse_settings(self, settings: Any):
             blur = int(settings.get('blur', blur))
         return area, threshold, interval, blur
 
-    def detect(self, detection_session: OpenCVDetectionSession, frame, src_size, convert_to_src_size) -> ObjectsDetected:
-        settings = detection_session.settings
+    def detect(self, frame, settings: Any, detection_session: OpenCVDetectionSession, src_size, convert_to_src_size) -> ObjectsDetected:
         area, threshold, interval, blur = self.parse_settings(settings)
 
         # see get_detection_input_size on undocumented size requirements for GRAY8
@@ -154,8 +152,8 @@ def detect(self, detection_session: OpenCVDetectionSession, frame, src_size, con
             # if w * h != contour_area:
             #     print("mismatch w/h", contour_area - w * h)
 
-            x2, y2, _ = convert_to_src_size((x + w, y + h))
-            x, y, _ = convert_to_src_size((x, y))
+            x2, y2 = convert_to_src_size((x + w, y + h))
+            x, y = convert_to_src_size((x, y))
             w = x2 - x + 1
             h = y2 - y + 1
 
@@ -206,11 +204,24 @@ def end_session(self, detection_session: OpenCVDetectionSession):
             detection_session.cap = None
         return super().end_session(detection_session)
 
-    async def run_detection_image(self, detection_session: DetectionSession, image: Image.Image, settings: Any, src_size, convert_to_src_size) -> Tuple[ObjectsDetected, Any]:
-        # todo
-        raise Exception('can not run motion detection on image')
-
-    async def run_detection_videoframe(self, videoFrame: VideoFrame, detection_session: OpenCVDetectionSession) -> ObjectsDetected:
+    async def generateObjectDetections(self, videoFrames: Any, session: ObjectDetectionGeneratorSession = None) -> Any:
+        try:
+            ds = OpenCVDetectionSession()
+            videoFrames = await scrypted_sdk.sdk.connectRPCObject(videoFrames)
+            async for videoFrame in videoFrames:
+               detected = await self.run_detection_videoframe(videoFrame, session and session.get('settings'), ds)
+               yield {
+                   '__json_copy_serialize_children': True,
+                   'detected': detected,
+                   'videoFrame': videoFrame,
+               }
+        finally:
+            try:
+                await videoFrames.aclose()
+            except:
+                pass
+
+    async def run_detection_videoframe(self, videoFrame: VideoFrame, settings: Any, detection_session: OpenCVDetectionSession) -> ObjectsDetected:
         width = videoFrame.width
         height = videoFrame.height
 
@@ -238,60 +249,8 @@ async def run_detection_videoframe(self, videoFrame: VideoFrame, detection_sessi
             'resize': resize,
         })
 
-        def convert_to_src_size(point, normalize = False):
-            return point[0] * scale, point[1] * scale, True
+        def convert_to_src_size(point):
+            return point[0] * scale, point[1] * scale
         mat = np.ndarray((height, width, self.pixelFormatChannelCount), buffer=buffer, dtype=np.uint8)
-        detections = self.detect(
-            detection_session, mat, (width, height), convert_to_src_size)
+        detections = self.detect(mat, settings, detection_session,  (width, height), convert_to_src_size)
         return detections
-
-    async def run_detection_avframe(self, detection_session: DetectionSession, avframe, settings: Any, src_size, convert_to_src_size) -> Tuple[ObjectsDetected, Any]:
-        if avframe.format.name != 'yuv420p' and avframe.format.name != 'yuvj420p':
-            mat = avframe.to_ndarray(format='gray8')
-        else:
-            mat = np.ndarray((avframe.height, avframe.width, self.pixelFormatChannelCount), buffer=avframe.planes[0], dtype=np.uint8)
-        detections = self.detect(
-            detection_session, mat, src_size, convert_to_src_size)
-        if not detections or not len(detections['detections']):
-            await self.detection_sleep(settings)
-            return None, None
-        return detections, None
-
-    async def run_detection_gstsample(self, detection_session: OpenCVDetectionSession, gst_sample, settings: Any, src_size, convert_to_src_size) -> ObjectsDetected:
-        buf = gst_sample.get_buffer()
-        caps = gst_sample.get_caps()
-        # can't trust the width value, compute the stride
-        height = caps.get_structure(0).get_value('height')
-        width = caps.get_structure(0).get_value('width')
-        result, info = buf.map(Gst.MapFlags.READ)
-        if not result:
-            return None, None
-        try:
-            mat = np.ndarray(
-                (height,
-                 width,
-                 self.pixelFormatChannelCount),
-                buffer=info.data,
-                dtype=np.uint8)
-            detections = self.detect(
-                detection_session, mat, src_size, convert_to_src_size)
-            # no point in triggering empty events.
-        finally:
-            buf.unmap(info)
-
-        if not detections or not len(detections['detections']):
-            await self.detection_sleep(settings)
-            return None, None
-        return detections, None
-
-    def create_detection_session(self):
-        return OpenCVDetectionSession()
-
-    async def detection_sleep(self, settings: Any):
-        area, threshold, interval, blur = self.parse_settings(settings)
-        # it is safe to block here because gstreamer creates a queue thread
-        await asyncio.sleep(interval / 1000)
-
-    async def detection_event_notified(self, settings: Any):
-        await self.detection_sleep(settings)
-        return await super().detection_event_notified(settings)

plugins/opencv/src/requirements.txt

@@ -3,10 +3,6 @@ numpy>=1.16.2
 # pillow for anything not intel linux
 Pillow>=5.4.1; sys_platform != 'linux' or platform_machine != 'x86_64'
 pillow-simd; sys_platform == 'linux' and platform_machine == 'x86_64'
-PyGObject>=3.30.4; sys_platform != 'win32'
 imutils>=0.5.0
 # not available on armhf
-av>=10.0.0; sys_platform != 'linux' or platform_machine == 'x86_64' or platform_machine == 'aarch64'
-# not available on armhf
-opencv-python; sys_platform != 'linux' or platform_machine == 'x86_64' or platform_machine == 'aarch64'
-
+opencv-python; sys_platform != 'linux' or platform_machine == 'x86_64'