def run(self):
detector = ObjectDetection(
) if self.type_file == "img" else VideoObjectDetection()
settings = QSettings(CONFIG_FILE_NAME, QSettings.IniFormat)
model = settings.value(KEY_SAVE_MODEL, MODELS[0], type=str)
if model == MODELS[0]:
detector.setModelTypeAsRetinaNet()
file = MODEL_RETINA_NET
elif model == MODELS[1]:
detector.setModelTypeAsYOLOv3()
file = MODEL_YOLOv3
else:
detector.setModelTypeAsTinyYOLOv3()
file = MODEL_TINY_YOLOv3
detector.setModelPath(file)
detector.loadModel(self.window.detection_speed)
if self.type_file == "img":
detections = detector.detectObjectsFromImage(
input_image=self.new_file,
output_image_path=self.output_file,
**self.window.getFunctionArg())
self._print_table_txt({
name: len(
list(
filter(
lambda elem: True
if elem["name"] == name else False, detections)))
for name in set([obj["name"] for obj in detections])
})
elif self.type_file == "video":
detector.detectObjectsFromVideo(
input_file_path=self.new_file,
output_file_path=self.output_file,
video_complete_function=self.forFull,
**self.window.getFunctionArg())
else:
camera = cv2.VideoCapture(self.window.index)
detector.detectObjectsFromVideo(
camera_input=camera,
output_file_path=self.output_file,
video_complete_function=self.forFull,
**self.window.getFunctionArg())
exec_path = os.getcwd()
detector = ObjectDetection()
detector.setModelTypeAsRetinaNet()
detector.setModelPath(os.path.join(exec_path, "resnet50_coco_best_v2.0.1.h5"))
detector.loadModel()
list = detector.detectCustomObjectsFromImage(
input_image=os.path.join(exec_path, "objects.jpg"),
output_image_path=os.path.join(exec_path, "new_objects.jpg"),
minimum_percentage_probability=70,
display_percentage_probability=True,
display_object_name=False)
from imageai.Detection import VideoObjectDetection
import os
execution_path = os.getcwd()
detector = VideoObjectDetection()
detector.setModelTypeAsYOLOv3()
detector.setModelPath(os.path.join(execution_path, "yolo.h5"))
detector.loadModel()
video_path = detector.detectObjectsFromVideo(
input_file_path=os.path.join(execution_path, "traffic.mp4"),
output_file_path=os.path.join(execution_path, "traffic_detected"),
frames_per_second=20,
log_progress=True)
print(video_path)
