Integration of offline video to full DLStream

Author: JensBlack

DeepLabStream.py

@@ -18,7 +18,7 @@
 import click
 
 from utils.configloader import RESOLUTION, FRAMERATE, OUT_DIR, MODEL,  MULTI_CAM, STACK_FRAMES, \
-    ANIMALS_NUMBER, STREAMS, EXP_NUMBER
+    ANIMALS_NUMBER, STREAMS, EXP_NUMBER, VIDEO
 from utils.poser import load_deeplabcut, get_pose, find_local_peaks_new, calculate_skeletons
 from utils.plotter import plot_bodyparts, plot_metadata_frame
 from experiments.experiments import ExampleExperiment
@@ -127,41 +127,47 @@ def set_camera_manager():
         ! Camera managers cannot be mixed
         :return: the chosen camera manager
         """
-        manager_list = []
-        # loading realsense manager, if installed
-        realsense = find_spec("pyrealsense2") is not None
-        if realsense:
-            from utils.realsense import RealSenseManager
-            realsense_manager = RealSenseManager()
-            manager_list.append(realsense_manager)
-
-        # loading basler manager, if installed
-        pylon = find_spec("pypylon") is not None
-        if pylon:
-            from utils.pylon import PylonManager
-            pylon_manager = PylonManager()
-            manager_list.append(pylon_manager)
-
-        def check_for_cameras(camera_manager):
-            """
-            Helper method to get cameras, connected to that camera manager
-            """
-            cameras = camera_manager.get_connected_devices()
-            if cameras:
-                print("Found {} {} camera(s)!".format(len(cameras), camera_manager.get_name()))
-                return True
-            else:
-                return False
 
-        # checking for connected cameras for all installed managers
-        for manager in manager_list:
-            if check_for_cameras(manager):
-                return manager
+        if VIDEO:
+            from utils.generic import VideoManager
+            manager = VideoManager()
+            return manager
         else:
-            # if no camera is found, try generic openCV manager
-            from utils.generic_camera import GenericManager
-            generic_manager = GenericManager()
-            return generic_manager
+            manager_list = []
+            # loading realsense manager, if installed
+            realsense = find_spec("pyrealsense2") is not None
+            if realsense:
+                from utils.realsense import RealSenseManager
+                realsense_manager = RealSenseManager()
+                manager_list.append(realsense_manager)
+
+            # loading basler manager, if installed
+            pylon = find_spec("pypylon") is not None
+            if pylon:
+                from utils.pylon import PylonManager
+                pylon_manager = PylonManager()
+                manager_list.append(pylon_manager)
+
+            def check_for_cameras(camera_manager):
+                """
+                Helper method to get cameras, connected to that camera manager
+                """
+                cameras = camera_manager.get_connected_devices()
+                if cameras:
+                    print("Found {} {} camera(s)!".format(len(cameras), camera_manager.get_name()))
+                    return True
+                else:
+                    return False
+
+            # checking for connected cameras for all installed managers
+            for manager in manager_list:
+                if check_for_cameras(manager):
+                    return manager
+            else:
+                # if no camera is found, try generic openCV manager
+                from utils.generic import GenericManager
+                generic_manager = GenericManager()
+                return generic_manager
 
     @property
     def cameras(self):

settings.ini

@@ -1,18 +1,19 @@
 [Streaming]
-RESOLUTION = 848, 480
-FRAMERATE = 30
+RESOLUTION = 320, 256
+FRAMERATE = 169
 STREAMS = color, depth, infrared
 OUTPUT_DIRECTORY = /Output
 MULTIPLE_DEVICES = False
 CAMERA_SOURCE = 2
 
 [DeepLabCut]
-DLC_PATH = /DeepLabCut/deeplabcut
-MODEL = Your_network_name
+DLC_PATH = D:\maDeepLabCut\deeplabcut
+MODEL = 13PointsFeb3-trainset95shuffle1_MobileNetV2
 
 [Experiment]
 EXP_NUMBER = 1
 RECORD_EXP = True
 
 [Video]
-VIDEO_SOURCE = /Offline_Test_video.avi
+VIDEO_SOURCE = PATH_TO_PRERECORDED_VIDEO
+VIDEO = False

utils/configloader.py

@@ -47,6 +47,8 @@ def get_script_path():
 
 # Video
 VIDEO_SOURCE = dsc_config['Video'].get('VIDEO_SOURCE')
+VIDEO = dsc_config['Video'].getboolean('VIDEO')
+
 
 # experiment
 EXP_NUMBER = dsc_config['Experiment'].getint('EXP_NUMBER')

utils/generic_camera.py utils/generic.pyutils/generic_camera.py renamed to utils/generic.py

@@ -7,8 +7,9 @@
 """
 
 import cv2
-from utils.configloader import CAMERA_SOURCE
-
+from utils.configloader import CAMERA_SOURCE, VIDEO_SOURCE, RESOLUTION, FRAMERATE
+import time
+import numpy as np
 
 class GenericManager:
     """
@@ -85,3 +86,47 @@ def get_name(self) -> str:
         return self._manager_name
 
 
+
+class VideoManager(GenericManager):
+
+    """
+    Camera manager class for analyzing videos
+    """
+    def __init__(self):
+        """
+        Generic video manager from video files
+        Uses pure opencv
+        """
+        self._manager_name = "generic"
+        self._camera = cv2.VideoCapture(VIDEO_SOURCE)
+        self._camera_name = "Video"
+        self.initial_wait = False
+        self.last_frame_time = time.time()
+
+
+    def get_frames(self) -> tuple:
+        """
+        Collect frames for camera and outputs it in 'color' dictionary
+        ***depth and infrared are not used here***
+        :return: tuple of three dictionaries: color, depth, infrared
+        """
+
+        color_frames = {}
+        depth_maps = {}
+        infra_frames = {}
+        ret, image = self._camera.read()
+        self.last_frame_time = time.time()
+        print(ret)
+        if ret:
+            if not self.initial_wait:
+                cv2.waitKey(1000)
+                self.initial_wait = True
+            image = cv2.resize(image, RESOLUTION)
+            color_frames[self._camera_name] = image
+            running_time = time.time() - self.last_frame_time
+            if running_time <= 1 / FRAMERATE:
+                sleepy_time = int(np.ceil(1000/FRAMERATE - running_time / 1000))
+                cv2.waitKey(sleepy_time)
+
+        return color_frames, depth_maps, infra_frames
+