rm pycache

.ipynb_checkpoints/gstreamer camera improve-checkpoint.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dc84920a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0bc9ac0c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "source = \"rtsp://192.168.5.218/txg/01\"\n",
+    "framerate = 60"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f7607446",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gst_format = f'rtspsrc location={source} latency=0 protocols=tcp ! ' \n",
+    "gst_format += 'rtph265depay ! h265parse ! nvv4l2decoder skip-frames=1 ! nvvidconv ! '\n",
+    "gst_format += f' video/x-raw,format=BGRx ! videorate ! video/x-raw,framerate={framerate}/1 ! videoconvert ! video/x-raw,format=BGR ! '\n",
+    "gst_format += 'appsink sync=false'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d9df82f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dev = cv2.VideoCapture(gst_format, cv2.CAP_GSTREAMER)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf294fdb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "while(dev.isOpened()):\n",
+    "    ret,frame = dev.read()\n",
+    "    if(ret):\n",
+    "        cv2.imshow(\"frame\", frame)\n",
+    "        if(cv2.waitKey(1000//framerate) == ord('q')):\n",
+    "            break\n",
+    "    else:\n",
+    "        break\n",
+    "        \n",
+    "dev.release()\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2d377c68",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f6c5d62c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "84ef06e2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

AlprTritonClient/EZLPRDataCollection.py

+# import common
+
+# from retina_utils.TrtRetinaPlate import TrtRetinaPlate
+import sys
+import os
+root_path=os.path.dirname(__file__)
+sys.path.append(root_path)
+# from retina_utils.TrtRetinaGrayPlate import TrtRetinaPlate as TrtRetinaGrayPlate
+# from retina_utils.TrtRetinaGrayPlateSHM import TrtRetinaPlateSHM as TrtRetinaGrayPlateSHM
+
+from retina_utils.TrtRetinaColorPlate import TrtRetinaPlate as TrtRetinaColorPlate
+from retina_utils.TrtRetinaColorPlateSHM import TrtRetinaPlateSHM as TrtRetinaColorPlateSHM 
+
+
+from ocr_utils.TrtCtcOcr import TrtCtcOcr
+from ocr_utils.TrtCtcOcrSHM import TrtCtcOcrSHM
+
+import cv2
+import numpy as np
+import time
+import threading, queue
+
+class TrtRetinaPlateThread(threading.Thread):
+    """TrtThread
+    This implements the child thread which continues to read images
+    from cam (input) and to do TRT engine inferencing.  The child
+    thread stores the input image and detection results into global
+    variables and uses a condition varaiable to inform main thread.
+    In other words, the TrtThread acts as the producer while the
+    main thread is the consumer.
+
+    """
+    def __init__(self, condition, vehicles_q, plates_q, conf_th=0.9, budget=10):
+        """__init__
+        # Arguments
+            condition: the condition variable used to notify main
+                       thread about new frame and detection result
+            cam: the camera object for reading input image frames
+            model: a string, specifying the TRT SSD model
+            conf_th: confidence threshold for detection
+        """
+        threading.Thread.__init__(self)
+        self.condition = condition
+        self.vehicles_q = vehicles_q
+        self.plates_q = plates_q
+        self.conf_th = conf_th
+        self.trt_plate = None   # to be created when run
+        self.running = False
+
+    def run(self):
+        """Run until 'running' flag is set to False by main thread.
+        NOTE: CUDA context is created here, i.e. inside the thread
+        which calls CUDA kernels.  In other words, creating CUDA
+        context in __init__() doesn't work.
+        """
+        global s_img, s_boxes, s_confs, s_lands
+
+        print('TrtThread: loading the TRT RetinaPlate engine...')
+#         self.trt_plate = TrtRetinaGrayPlate((320,320))
+#        self.trt_plate = TrtRetinaGrayPlateSHM((320,320))
+        self.trt_plate = TrtRetinaColorPlateSHM((320,320))
+        
+        print('TrtThread: TRT RetinaPlate start running...')
+        self.running = True
+        while self.running:
+            if(self.vehicles_q.empty()):
+                time.sleep(1)
+                continue
+            info = self.vehicles_q.get()
+            if(not isinstance(info, VehicleInfo)):
+                continue
+            if(info.vechile_img is None):
+                continue
+            output = self.trt_plate.detect(info.vechile_img, self.conf_th)
+            if(output.shape[0] > 0):
+                boxes = output[:,:4].astype(int)
+                confs = output[:,4]
+                lands = output[:,5:].astype(int)
+                loc = boxes[0]
+                crop_img = info.vechile_img[loc[1]:loc[3],loc[0]:loc[2]]
+                # 過濾物件
+                plateInfo = PlateInfo(info.track_id, info.img, info.vechile_img, crop_img)
+                self.plates_q.put(plateInfo)
+#             with self.condition:
+#                 s_img, s_boxes, s_confs, s_lands = info.img, boxes, confs, lands
+#                 self.condition.notify()
+        del self.trt_plate
+        print('TrtThread: stopped...')
+
+    def stop(self):
+        self.running = False
+        self.join()
+        
+class TrtCTCOCRThread(threading.Thread):
+    """TrtThread
+    This implements the child thread which continues to read images
+    from cam (input) and to do TRT engine inferencing.  The child
+    thread stores the input image and detection results into global
+    variables and uses a condition varaiable to inform main thread.
+    In other words, the TrtThread acts as the producer while the
+    main thread is the consumer.
+    """
+    def __init__(self, condition, plates_q, results_q, budget=10):
+        """__init__
+        # Arguments
+            condition: the condition variable used to notify main
+                       thread about new frame and detection result
+            cam: the camera object for reading input image frames
+            model: a string, specifying the TRT SSD model
+            conf_th: confidence threshold for detection
+        """
+        threading.Thread.__init__(self)
+        self.condition = condition
+        self.plates_q = plates_q
+        self.results_q = results_q
+        self.trt_ocr = None   # to be created when run
+        self.running = False
+        
+        self.save_path = "/media/aaeon/Data/samples"
+
+    def run(self):
+        """Run until 'running' flag is set to False by main thread.
+        NOTE: CUDA context is created here, i.e. inside the thread
+        which calls CUDA kernels.  In other words, creating CUDA
+        context in __init__() doesn't work.
+        """
+#         global s_img, s_boxes, s_confs, s_lands
+
+        print('TrtThread: loading the TRT CTC OCR engine...')
+#         self.trt_ocr = TrtCtcOcr()
+        self.trt_ocr = TrtCtcOcrSHM()
+        
+        
+        print('TrtThread: TRT CTC OCR start running...')
+        self.running = True
+        while self.running:
+            if(self.plates_q.empty()):
+                time.sleep(1)
+                continue
+            info = self.plates_q.get()
+            
+            if(not isinstance(info, PlateInfo)):
+                continue
+            if(info.plate_img is None):
+                continue
+#             stime = time.time()
+            try:
+                plate = self.trt_ocr.recognition(info.plate_img)
+            except Exception as e:
+                print(e)
+                plate = ""
+#             print("Resnet32 CTC OCR 480*16 shared memory inference time", time.time() - stime)
+            
+            resultInfo = ResultInfo(info.track_id, plate, info.vechile_img, info.plate_img)
+            
+            if(resultInfo.plate is not None and resultInfo.plate_img is not None):
+                fullscreen_save_path = os.path.join(self.save_path, "fullscreen", "{}_{}.jpg".format(resultInfo.track_id, resultInfo.plate))
+                vehicle_save_path = os.path.join(self.save_path, "vehicles", "{}_{}.jpg".format(resultInfo.track_id, resultInfo.plate))
+                plate_save_path = os.path.join(self.save_path, "plates", "{}_{}.jpg".format(resultInfo.track_id, resultInfo.plate))
+                
+                cv2.imwrite(fullscreen_save_path, info.img)
+                cv2.imwrite(vehicle_save_path, resultInfo.vechile_img)
+                cv2.imwrite(plate_save_path, resultInfo.plate_img)
+                
+            
+            self.results_q.put(resultInfo)
+#             with self.condition:
+#                 s_img, s_boxes, s_confs, s_lands = img, boxes, confs, lands
+#                 self.condition.notify()
+        del self.trt_ocr
+        print('TrtThread: stopped...')
+
+    def stop(self):
+        self.running = False
+        self.join()
+        
+        
+class VehicleInfo(object):
+    def __init__(self,track_id, img, vechile_img):
+        self.track_id = track_id
+        self.img = img
+        self.vechile_img = vechile_img
+        
+class PlateInfo(object):
+    def __init__(self,track_id, img, vechile_img, plate_img):
+        self.track_id = track_id
+        self.img = img
+        self.vechile_img = vechile_img
+        self.plate_img = plate_img
+        
+class ResultInfo(object):
+    def __init__(self,track_id, plate,vechile_img, plate_img):
+        self.track_id = track_id
+        self.plate = plate
+        self.vechile_img = vechile_img
+        self.plate_img = plate_img
+        
+        
+class EZLPR(object):    
+    def __init__(self):
+        self.vehiclesQueue = queue.Queue()
+        self.platesQueue = queue.Queue()
+        self.resultsQueue = queue.Queue()
+        
+        condition = threading.Condition() # condition 暫時用不到
+        self.trtRetinaPlateThread = TrtRetinaPlateThread(condition, self.vehiclesQueue, self.platesQueue)
+        self.trtCtcOcrThread =  TrtCTCOCRThread(condition, self.platesQueue, self.resultsQueue)
+        self.trtRetinaPlateThread.start()  # start the child thread
+        self.trtCtcOcrThread.start()
+        
+    def put(self, track_id, img, crop_img):
+        vehicleInfo = VehicleInfo(track_id = track_id, img = img, vechile_img = crop_img)
+        self.vehiclesQueue.put(vehicleInfo)
+        
+    def out(self):
+        while not self.resultsQueue.empty():
+            resultInfo = self.resultsQueue.get()
+            yield resultInfo.track_id,resultInfo.plate, resultInfo.vechile_img, resultInfo.plate_img
+            
+    def __del__(self):
+        self.trtRetinaPlateThread.stop()
+        self.trtCtcOcrThread.stop()
\ No newline at end of file

PlanB_test0613.py

@@ -38,10 +38,10 @@ easyLPR=EZLPR()
 # source="/home/aaeon/Kevin_Car.MOV"
 #source = "../Ch17-20220314-190000.mp4"
 
-# source="rtsp://192.168.5.218/txg/01"
-source="rtsp://140.120.65.31/live.sdp"
-# cam=Camera(1,source,encoder = "h265",width=1920,height=1080)
-cam=Camera(1,source,encoder = "h264",width=1920,height=1080)
+source="rtsp://192.168.5.218/txg/01"
+# source="rtsp://140.120.65.31/live.sdp"
+cam=Camera(1,source,encoder = "h265",width=1920,height=1080, use_gstr=True, framerate=60, skip_frames=1)
+# cam=Camera(1,source,encoder = "h264",width=1920,height=1080)
 
 camera_id=1
 break_flag=False

VideoAnalysis/Camera_Jetson.py

@@ -4,7 +4,32 @@ from queue import Queue
 import time, numpy as np, cv2
         
 class Camera(object):
-    def __init__(self,_id,video_path,encoder=None, width=1280, height=720, framerate=30, log=None, maxsize=10 , use_gstr=True):
+    """
+    jetson平台相機物件，透過threading去處理影像，並儲放於Queue之中，並支援多種格式
+    
+    Args:
+    
+    video_path: 來源包含影片、串流
+    
+    encoder: 解碼器選擇，h264或h265
+    
+    width: 輸出影像的寬
+    
+    height: 輸出影像的高
+    
+    framerate: 輸出影像的更新率
+    
+    log: 自定義log 函數
+    
+    maxsize: queue(buffer)最大存放大小
+    
+    use_gstr: 是否使用gstreamer後台
+    
+    skip_frames: 是否跳過部分幀，1 => 全部解碼， 2 => 只解碼 non-ref frames，3 => 只解碼 key-frames
+    
+    
+    """
+    def __init__(self,_id,video_path,encoder=None, width=1280, height=720, framerate=30, log=None, maxsize=10 , use_gstr=True, skip_frames=1):
         self.ID = _id
         self.__log = self.__log if log is None else log
         self.__isCaptured = False
@@ -16,6 +41,7 @@ class Camera(object):
         self.framerate = framerate
         self.encoder = encoder
         self.use_gstr = use_gstr
+        self.skip_frames = skip_frames
         self.__thread = Thread(target=self.__job)
         self.resultQueue = Queue(maxsize=maxsize)
     def start(self):
@@ -34,7 +60,7 @@ class Camera(object):
         h = self.height
         fps = self.framerate
         if self.use_gstr:
-            source = self.__gstreamer(self.video_path,w, h, fps)
+            source = self.__gstreamer(self.video_path,w, h, fps, skip_frames = self.skip_frames)
         while self.isOpened:
             try:
                 if self.use_gstr:
@@ -67,7 +93,7 @@ class Camera(object):
         self.__frame = None
         self.__log("camera stop")
         
-    def __gstreamer(self, source=0,width=1280, height=720, framerate=30, flip_method=2):        
+    def __gstreamer(self, source=0,width=1280, height=720, framerate=30, flip_method=2, skip_frames = 1):        
         if source==0:
             # Camera Device Stream
             return (
@@ -86,15 +112,16 @@ class Camera(object):
             if self.encoder=="h265":
                 print("h265")
                 return (
-                   f'rtspsrc location={source} ! ' +
+                   f'rtspsrc location={source} latency=0 protocols=tcp ! ' +
 #                    'watchdog timeout=10000 !'+
-                   'rtph265depay ! h265parse ! nvv4l2decoder ! nvvidconv ! '+
-                   'video/x-raw,format=BGRx ! videoconvert ! video/x-raw,format=BGR ! appsink'
+                   f'rtph265depay ! h265parse ! nvv4l2decoder skip-frames={skip_frames} ! nvvidconv ! '+
+                   f' video/x-raw,format=BGRx ! videorate ! video/x-raw,framerate={framerate}/1 ! videoconvert ! video/x-raw,format=BGR ! '+
+                   'appsink sync=false'
                )
             elif self.encoder=="h264":
                 print("h264")
                 gst_str = ('rtspsrc location={} latency={} ! '
-                   'rtph264depay ! h264parse ! omxh264dec ! '
+                   f'rtph264depay ! h264parse ! nvv4l2decoder skip-frames={skip_frames}! '
                    'nvvidconv ! '
                    'video/x-raw, width=(int){}, height=(int){}, '
                    'format=(string)BGRx ! '

gstream_rtsp_test.py

+import cv2
+
+source = "rtsp://192.168.5.218/txg/01"
+framerate = 30
+skipframes = 0
+
+gst_format = f'rtspsrc location={source} latency=0 protocols=tcp ! ' 
+gst_format += f'rtph265depay ! h265parse ! nvv4l2decoder skip-frames={skipframes} ! nvvidconv ! '
+gst_format += f' video/x-raw,format=BGRx ! videorate ! video/x-raw,framerate={framerate}/1 ! videoconvert ! video/x-raw,format=BGR ! '
+gst_format += 'appsink sync=false'
+
+dev = cv2.VideoCapture(gst_format, cv2.CAP_GSTREAMER)
+
+if(dev.isOpened()):
+    print("strat stream")
+    
+else:
+    print("Open this source faild")
+    
+dev.release()
\ No newline at end of file

gstreamer camera improve.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dc84920a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0bc9ac0c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "source = \"rtsp://192.168.5.218/txg/01\"\n",
+    "framerate = 60"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f7607446",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gst_format = f'rtspsrc location={source} latency=0 protocols=tcp ! ' \n",
+    "gst_format += 'rtph265depay ! h265parse ! nvv4l2decoder skip-frames=2 ! nvvidconv ! '\n",
+    "gst_format += f' video/x-raw,format=BGRx ! videorate ! video/x-raw,framerate={framerate}/1 ! videoconvert ! video/x-raw,format=BGR ! '\n",
+    "gst_format += 'appsink sync=false'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d9df82f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dev = cv2.VideoCapture(gst_format, cv2.CAP_GSTREAMER)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf294fdb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "while(dev.isOpened()):\n",
+    "    ret,frame = dev.read()\n",
+    "    if(ret):\n",
+    "        cv2.imshow(\"frame\", frame)\n",
+    "        if(cv2.waitKey(1000//framerate) == ord('q')):\n",
+    "            break\n",
+    "    else:\n",
+    "        break\n",
+    "        \n",
+    "dev.release()\n",
+    "cv2.destroyAllWindows()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2d377c68",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f6c5d62c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "84ef06e2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}