bump
This commit is contained in:
The Bears
188
run_me.py
188
run_me.py
@@ -2,7 +2,6 @@ import numpy as np
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from functools import partial
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from hailo_platform import VDevice, HailoSchedulingAlgorithm, FormatType
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import cv2
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import numpy as np
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@@ -33,7 +32,6 @@ def resize_image(img_in, reshape_to_final=True):
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return data
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def model_scoring_callback(completion_info, bindings, data):
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if completion_info.exception:
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# handle exception
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@@ -83,9 +81,11 @@ import multiprocessing
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import numpy as np
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import ctypes
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import shutil
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from utils import *
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cameras = {
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"camera_side": {
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'url': "rtsp://admin:marybear@192.168.1.151:554/h264Preview_01_sub",
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"camera_sidefeeder": {
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'url': "rtsp://admin:marybear@192.168.1.157:554/h264Preview_01_sub",
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'resolution': (480, 640, 3)
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},
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"camera_driveway": {
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@@ -111,66 +111,93 @@ cameras = {
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},
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}
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# # %%
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# import os
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# os.environ['OPENCV_FFMPEG_CAPTURE_OPTIONS'] = 'rtsp_transport;udp'
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# cap = cv2.VideoCapture(cameras['camera_railing']['url'])
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# # %%
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# while True:
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# _, frame = cap.read()
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# # %%
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# _, frame = cap.read()
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# cv2.imwrite('FRAME.jpg', frame)
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# # %%
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def format_gst_url(rtsp_url):
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gst_pipeline = f"rtspsrc location={rtsp_url} latency=50 ! rtph264depay ! h264parse ! avdec_h264 ! videoconvert ! appsink max-buffers=1 drop=true"
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return gst_pipeline
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from functools import partial
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cameras = dict()
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for cam_name, details in cameras.items():
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array_len = np.prod(details['resolution'])
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rtsp_url = details['url']
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resolution = details['resolution']
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cameras[cam_name] = StreamManager( rtsp_url, resolution, cam_name)
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# %%
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details['cam_name'] = cam_name
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details['img_array'] = multiprocessing.Array(ctypes.c_uint8,
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int(array_len), lock = True)
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int(array_len),
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lock=True)
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details['img_timestamp'] = multiprocessing.Value(ctypes.c_double)
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details['queue'] = multiprocessing.Queue()
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details['gst_pipeline_str'] = format_gst_url(details['url'])
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details['rtsp_url'] = format_ffmpeg_decode_url(details['url']).split(" ")
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details['process_func'] = partial(stream_wrapper,
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details['resolution'],
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details['rtsp_url'],
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camera_name=cam_name,
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queue=details['queue'],
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img_array=details['img_array'],
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img_timestamp=details['img_timestamp'])
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for cam_name, details in cameras.items():
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p = multiprocessing.Process(target = details['process_func'])
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details['process'] = p
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p.start()
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# %%
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img_array = details['img_array']
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img_timestamp = details['img_timestamp']
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import time
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with img_timestamp.get_lock():
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img_timestamp.value = -1
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details['queue'].put('get')
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for i in range(1000):
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val = img_timestamp.value
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print(val)
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if val > 0:
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print('Done')
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break
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time.sleep(0.001)
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import datetime as dt
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def rtsp_stream_manager( camera_name, gst_pipeline_str, queue, img_array, img_timestamp):
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capture_handle = cv2.VideoCapture(gst_pipeline_str, cv2.CAP_GSTREAMER)
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while True:
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if not queue.empty():
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msg = queue.get_nowait()
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if msg == 'get':
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ret, frame = capture_handle.read()
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with img_timestamp.get_lock(), img_array.get_lock():
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if frame is None:
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print(f"Read empty frame for {camera_name}")
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img_array[:] = 0
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img_timestamp.value = 0
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else:
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print(f"Read frame for {camera_name} at {dt.datetime.now()}")
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img_array[:] = frame.flatten()[:]
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img_timestamp.value = time.time()
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elif msg == 'restart':
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print('Restarting')
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capture_handle = cv2.VideoCapture(gst_pipeline_str, cv2.CAP_GSTREAMER)
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elif msg == 'exit':
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print('Exiting')
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return
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# %%
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for cam_name, details in cameras.items():
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details['queue'].put('get')
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img_array = details['img_array']
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img_timestamp = details['img_timestamp']
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with img_array.get_lock(), img_timestamp.get_lock():
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reshaped_image = np.frombuffer(details['img_array'].get_obj(),
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dtype=np.uint8).reshape(
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details['resolution'])
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timestamp = img_timestamp.value
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img_timestamp.value = -1
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print('Writing for ' + cam_name + f' for {reshaped_image.shape}')
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cv2.imwrite('images/'+ cam_name + '.jpg', reshaped_image)
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# %%
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import asyncio
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img_scoring_queue = multiprocessing.Queue()
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for cam_name, details in cameras.items():
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p = multiprocessing.Process(target=rtsp_stream_manager,
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args=(cam_name, details['gst_pipeline_str'],
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details['queue'], details['img_array'], details['img_timestamp']))
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details['queue'], details['img_array'],
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details['img_timestamp']))
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details['process'] = p
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asyncio.create_task(details['async_task'])
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shape = (512, 896, 3)
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asyncio.run(read_stream(shape, cmd))
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import datetime as dt
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for cam_name, details in cameras.items():
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details['process'].start()
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# %%
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@@ -180,60 +207,49 @@ for cam_name, details in cameras.items():
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for cam_name, details in cameras.items():
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details['queue'].put('get')
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if os.path.exists('images/'):
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shutil.rmtree('images/')
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os.makedirs('images/')
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os.makedirs('images/')
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def create_score_message( details, reshaped_image, timestamp):
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def create_score_message(details, reshaped_image, timestamp):
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frames = list()
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msg = list()
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if details.get('split_into_two', False):
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split_point = int(reshaped_image.shape[1]/2)
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left_frame = resize_image(reshaped_image[:,:split_point,:], reshape_to_final = False)
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right_frame = resize_image(reshaped_image[:,split_point:,:], reshape_to_final = False)
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split_point = int(reshaped_image.shape[1] / 2)
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left_frame = resize_image(reshaped_image[:, :split_point, :],
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reshape_to_final=False)
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right_frame = resize_image(reshaped_image[:, split_point:, :],
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reshape_to_final=False)
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left_frame = cv2.cvtColor(left_frame, cv2.COLOR_BGR2RGB)
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right_frame = cv2.cvtColor(right_frame, cv2.COLOR_BGR2RGB)
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msg.append({'camera_name': details['cam_name']+'_left', 'frame': left_frame, 'image_timestamp': timestamp})
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msg.append({'camera_name': details['cam_name']+'_right', 'frame': right_frame, 'image_timestamp': timestamp})
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right_frame = cv2.cvtColor(right_frame, cv2.COLOR_BGR2RGB)
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msg.append({
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'camera_name': details['cam_name'] + '_left',
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'frame': left_frame,
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'image_timestamp': timestamp
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})
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msg.append({
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'camera_name': details['cam_name'] + '_right',
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'frame': right_frame,
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'image_timestamp': timestamp
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})
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else:
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frame = resize_image(reshaped_image, reshape_to_final = False)
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frame = resize_image(reshaped_image, reshape_to_final=False)
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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msg.append({'camera_name': details['cam_name'], 'frame': frame, 'image_timestamp': timestamp})
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msg.append({
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'camera_name': details['cam_name'],
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'frame': frame,
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'image_timestamp': timestamp
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})
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return msg
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for cam_name, details in cameras.items():
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img_array = details['img_array']
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img_timestamp = details['img_timestamp']
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with img_array.get_lock(), img_timestamp.get_lock():
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reshaped_image = np.frombuffer(details['img_array'].get_obj(), dtype=np.uint8).reshape(details['resolution'])
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timestamp = img_timestamp.value
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for msg in create_score_message(details, reshaped_image, timestamp):
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img_scoring_queue.put(msg)
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print('Writing for ' + cam_name + f' for {reshaped_image.shape}')
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# cv2.imwrite('images/'+ cam_name + '.jpg', reshaped_image)
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for x in range(img_scoring_queue.qsize()):
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qu = img_scoring_queue.get()
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print(qu['camera_name'],qu['frame'].shape)
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cv2.imwrite(str(x)+'.jpg', qu['frame'])
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qu = img_scoring_queue.get()
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print(qu['camera_name'], qu['frame'].shape)
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cv2.imwrite(str(x) + '.jpg', qu['frame'])
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