def __init__(self, name, in_video: VideoReader, state: State, video_path,
fps, frame_size, coord, answer):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.coord = coord
self.fps = fps
self.frame_size = tuple(frame_size)
self.out_video = VideoWriter("VideoWriter", video_path, self.fps,
self.frame_size)
self.sleep_time_vis = 1. / self.fps
self.in_video = in_video
self.stopped = True
self.visualize_thread = None
self.predictor = Predictor()
self.visualizer = Visualizer()
self.answer = answer
self.best_accuracy = 0
self.best_frame = -1
self.best_result = ''
self.logger.info("Create VisualizeStream")
def __init__(self, name, state: State, video_reader: VideoReader):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.predictor = Predictor()
self.logger.info("Create OcrStream")
def __init__(self, name, state: State, video_reader: VideoReader):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.predictor = Predictor(
'C:\\Users\\user\\results\\experiment1\\model-052-1.928074.pth',
(32, 80)) #TODO: Your Predictor
self.logger.info("Create OcrStream")
self.time = None
self.frame_quantity = 0
def __init__(self, name, state: State, video_reader: VideoReader, model_path):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.time_start = datetime.now()
self.stopped = False
converter = strLabelConverter(CV_CONFIG.get('alphabet'))
self.predictor = Predictor(model_path, converter) #TODO: Your Predictor
self.logger.info("Create OcrStream")
class OcrStream:
def __init__(self, name, state: State, video_reader: VideoReader):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.predictor = Predictor()
self.logger.info("Create OcrStream")
def _ocr_loop(self):
try:
frame = self.video_reader.read()
pred = self.predictor.predict([frame])
self.state.text = pred
except Exception as e:
self.logger.exception(e)
self.state.exit_event.set()
def _start_ocr(self):
self.ocr_thread = Thread(target=self._ocr_loop)
self.ocr_thread.start()
def start(self):
self._start_ocr()
self.logger.info("Start OcrStream")
def stop(self):
if self.ocr_thread is not None:
self.ocr_thread.join()
self.logger.info("Stop OcrStream")
class OcrStream:
def __init__(
self,
name,
state: State,
video_reader: VideoReader,
model_path='/home/alex/final_version_ocr/project (car numbers)/model/model_crnn.pth'
):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.time_start = datetime.now()
self.stopped = False
converter = strLabelConverter(CV_CONFIG.get('alphabet'))
self.predictor = Predictor(model_path, converter)
self.logger.info("Create OcrStream")
def _ocr_loop(self):
try:
file = open("predictions.txt", "w")
while True:
if self.stopped:
file.close()
return
frame = self.video_reader.read()
pred = self.predictor.predict(frame[None])
file.writelines("%s\n" % pred)
self.state.text = pred
self.state.frame = frame
self.state.frame_id += 1
if self.state.frame_id % 24 == 0:
cur_t = datetime.now()
secs = (cur_t - self.time_start).seconds
self.logger.info(
f"FPS: {self.state.frame_id/secs if secs>0 else 0}")
file.close()
except Exception as e:
self.logger.exception(e)
self.state.exit_event.set()
def _start_ocr(self):
self.ocr_thread = Thread(target=self._ocr_loop)
self.ocr_thread.start()
def start(self):
self._start_ocr()
self.logger.info("Start OcrStream")
def stop(self):
self.stopped = True
if self.ocr_thread is not None:
self.ocr_thread.join()
self.logger.info("Stop OcrStream")
def __init__(
self,
name,
state: State,
video_reader: VideoReader,
model_path='/home/alex/final_version_ocr/project (car numbers)/model/model_crnn.pth'
):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.time_start = datetime.now()
self.stopped = False
converter = strLabelConverter(CV_CONFIG.get('alphabet'))
self.predictor = Predictor(model_path, converter)
self.logger.info("Create OcrStream")
class OcrStream:
def __init__(self, name, state: State, video_reader: VideoReader, model_path):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.time_start = datetime.now()
self.stopped = False
converter = strLabelConverter(CV_CONFIG.get('alphabet'))
self.predictor = Predictor(model_path, converter) #TODO: Your Predictor
self.logger.info("Create OcrStream")
def _ocr_loop(self):
try:
while True:
if self.stopped:
return
frame = self.video_reader.read()
pred = self.predictor.predict(frame[None])
self.state.text = pred
self.state.frame = frame
self.state.frame_id += 1
if self.state.frame_id % 24 == 0:
cur_t = datetime.now()
secs = (cur_t-self.time_start).seconds
self.logger.info(f"FPS: {self.state.frame_id/secs if secs>0 else 0}")
except Exception as e:
self.logger.exception(e)
self.state.exit_event.set()
def _start_ocr(self):
self.ocr_thread = Thread(target=self._ocr_loop)
self.ocr_thread.start()
def start(self):
self._start_ocr()
self.logger.info("Start OcrStream")
def stop(self):
self.stopped = True
if self.ocr_thread is not None:
self.ocr_thread.join()
self.logger.info("Stop OcrStream")
class OcrStream:
def __init__(self, name, state: State, video_reader: VideoReader):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.video_reader = video_reader
self.ocr_thread = None
self.predictor = Predictor(
'C:\\Users\\user\\results\\experiment1\\model-052-1.928074.pth',
(32, 80)) #TODO: Your Predictor
self.logger.info("Create OcrStream")
self.time = None
self.frame_quantity = 0
def _ocr_loop(self):
try:
self.start_time = time.time()
while True:
frame = self.video_reader.read()
pred = self.predictor.predict(frame)
self.state.text = pred
self.state.frame = frame
self.frame_quantity += 1
if self.frame_quantity % 10 == 0:
print(self.frame_quantity /
(time.time() - self.start_time))
except Exception as e:
self.logger.exception(e)
self.state.exit_event.set()
def _start_ocr(self):
self.ocr_thread = Thread(target=self._ocr_loop)
self.ocr_thread.start()
def start(self):
self._start_ocr()
self.logger.info("Start OcrStream")
def stop(self):
if self.ocr_thread is not None:
self.ocr_thread.join()
self.logger.info("Stop OcrStream")
},
"optimizer": ("Adam", {
"lr": 0.001
}),
# CHANGE DEVICE IF YOU USE GPU
"device":
"cpu",
}
if __name__ == "__main__":
converter = strLabelConverter(MODEL_PARAMS['alphabet'])
model_path = EXPERIMENT_DIR / sorted(
os.listdir(EXPERIMENT_DIR))[-1] # Last saved model
#print('Model path is', model_path)
#print('Is it a file?', os.path.isfile(model_path))
predictor = Predictor(model_path,
converter,
CV_CONFIG.get('ocr_image_size'),
device=MODEL_PARAMS['device'])
#print('File name', args.file_name)
#print(os.path.isdir('/workdir/data/CropNumbers'))
#print(os.path.isfile(args.file_name))
if os.path.isdir(args.file_name):
print('DIR Are not supported')
else:
img = imageio.imread(args.file_name)
print(f'Prediction "{predictor.predict(img)}"')
class VisualizeStream:
def __init__(self, name, in_video: VideoReader, state: State, video_path,
fps, frame_size, coord, answer):
self.name = name
self.logger = logging.getLogger(self.name)
self.state = state
self.coord = coord
self.fps = fps
self.frame_size = tuple(frame_size)
self.out_video = VideoWriter("VideoWriter", video_path, self.fps,
self.frame_size)
self.sleep_time_vis = 1. / self.fps
self.in_video = in_video
self.stopped = True
self.visualize_thread = None
self.predictor = Predictor()
self.visualizer = Visualizer()
self.answer = answer
self.best_accuracy = 0
self.best_frame = -1
self.best_result = ''
self.logger.info("Create VisualizeStream")
def _visualize(self):
try:
begin = datetime.now()
frame_num = 0
while True:
if self.stopped:
return
frame = self.in_video.read()
if frame is None:
self.state.exit_event.set()
end = datetime.now()
print('FRAMES: ', frame_num, end - begin)
return
prediction = self.predictor.predict(frame)
hits = 0
for i in range(6):
if len(prediction) > i and self.answer[i] == prediction[i]:
hits += 1
if hits > self.best_accuracy:
self.best_accuracy = hits
self.best_result = prediction
self.best_frame = frame_num
frame = self.visualizer(frame, prediction)
self.out_video.write(frame)
time.sleep(self.sleep_time_vis)
frame_num += 1
except Exception as e:
self.logger.exception(e)
self.state.exit_event.set()
def start(self):
self.logger.info("Start VisualizeStream")
self.stopped = False
self.visualize_thread = Thread(target=self._visualize, args=())
self.visualize_thread.start()
self.in_video.start()
def stop(self):
self.logger.info("Stop VisualizeStream")
self.stopped = True
self.out_video.stop()
if self.visualize_thread is not None:
self.visualize_thread.join()