def main():
print("Running Task")
camera = Camera()
d = Detector()
rs = d.detect_image(camera.capture())
print(rs)
for obj, confidence in rs.items():
print('Object {} : Confidence {}'.format(obj, confidence))
def test_detector_image(self):
# Create Localizer
cfg_path = './data/yolo/full/trafficsigns.cfg'
weights_path = './data/yolo/full/trafficsigns.weights'
threshold = 0.24
localizer = Localizer(cfg_path, weights_path, threshold, gpu=0.0)
# Create cropper
crop_percent = 0.25
force_square = True
cropper = Cropper(crop_percent, force_square)
# Create classifier
model_path = './data/classifier/trafficsigns.json'
weights_path = './data/classifier/trafficsigns.h5'
labels_path = './data/classifier/classes.txt'
threshold = 0.5
classifier = Classifier(model_path, weights_path, labels_path,
threshold)
# Create detection pipeline
detection_pipeline = DetectionPipeline(localizer, cropper, classifier)
# Create detector
images_path = './data/classifier/classes/'
sounds_path = './data/sounds/'
detector = Detector(detection_pipeline, images_path, sounds_path)
# Detect on image
img = cv2.imread('./tests/data/test.png')
image, detections = detector.detect_image(img,
show_confidence=True,
return_image=True)
true_detections = [{
'class_id': 15,
'coordinates': [1434, 456, 1590, 612],
'label': 'max-60',
'confidence': 1.0
}]
assert detections == true_detections
def test_detector_image_output_json(self):
# Create Localizer
cfg_path = './data/yolo/full/trafficsigns.cfg'
weights_path = './data/yolo/full/trafficsigns.weights'
threshold = 0.24
localizer = Localizer(cfg_path, weights_path, threshold, gpu=0.0)
# Create cropper
crop_percent = 0.25
force_square = True
cropper = Cropper(crop_percent, force_square)
# Create classifier
model_path = './data/classifier/trafficsigns.json'
weights_path = './data/classifier/trafficsigns.h5'
labels_path = './data/classifier/classes.txt'
threshold = 0.5
classifier = Classifier(model_path, weights_path, labels_path,
threshold)
# Create detection pipeline
detection_pipeline = DetectionPipeline(localizer, cropper, classifier)
# Create detector
images_path = './data/classifier/classes/'
sounds_path = './data/sounds/'
detector = Detector(detection_pipeline, images_path, sounds_path)
# Detect on image
img = cv2.imread('./tests/data/test.png')
output_filename = './tests/data/detector_image.json'
detections = detector.detect_image(img, output=output_filename)
assert os.path.exists(output_filename) == True
