def init():
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument('--classes',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
parser.add_argument(
'--image',
default=False,
action="store_true",
help='Image detection mode, will ignore all positional arguments')
'''
Command line positional arguments -- for video detection mode
'''
parser.add_argument("--input",
nargs='?',
type=str,
required=False,
default='./path2your_video',
help="Video input path")
parser.add_argument("--output",
nargs='?',
type=str,
default="",
help="[Optional] Video output path")
return parser
def start(path, file_extension, code):
YOLO.get_defaults("model_data/model1-tiny_last_weights.h5")
YOLO.get_defaults("tiny_yolo_anchors.txt")
YOLO.get_defaults("coco_classes.txt")
YOLO.get_defaults("gpu_num")
if file_extension == ".jpg" or file_extension == ".png" or file_extension == ".jpeg" or file_extension == ".JPG" or file_extension == ".JPEG":
"""
Image detection mode, disregard any remaining command line arguments
"""
print("Image detection mode")
print('img\nimg\nimg\nimg\nimg\nimg\nimg\nimg\nimg\n')
path_img, predicted_class, score_list, gesture, gesture_score = detect_img(
YOLO(), path, code)
return path_img, predicted_class, score_list, gesture, gesture_score
elif "input" in FLAGS:
print(FLAGS.input, 'vid\nvid\nvid\nvid\nvid\nvid\nvid\nvid\nvid\n')
detect_video(YOLO(**vars(FLAGS)), FLAGS.input, FLAGS.output)
else:
print(
"Must specify at least video_input_path. See usage with --help.")
n = len(annotation_lines)
if n == 0 or batch_size <= 0: return None
return data_generator(annotation_lines, batch_size, input_shape, anchors,
num_classes)
if __name__ == '__main__':
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
# Command line options
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
parser.add_argument('--class_path',
type=str,
help='Text file with class names one per line.')
parser.add_argument(
'--data_path',
type=str,
help='Azure ML path to Storage passed from datastore mount in driver.')
parser.add_argument(
'--data_dir',
type=str,
default='data',
help=
# r_image.show()
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument('--classes',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
num_classes):
n = len(annotation_lines)
if n == 0 or batch_size <= 0: return None
return data_generator(annotation_lines, batch_size, input_shape, anchors,
num_classes)
if __name__ == '__main__':
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
# Command line options
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
parser.add_argument('--annot_path',
type=str,
help='Annotation file with image location and bboxes')
parser.add_argument('--class_path',
type=str,
help='Text file with class names one per line')
parser.add_argument(
r_image = yolo.detect_image(image)
r_image.save(nom)
j=j+1
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
parser.add_argument('--model', type=str,default='weights_yolo_train/trained_weights_stage_1.h5',
help='path to model weight file, default ' + YOLO.get_defaults("model_path"))
parser.add_argument('--anchors', type=str,default='model_data/yolo_anchors.txt',
help='path to anchor definitions, default '
+ YOLO.get_defaults('anchors_path'))
parser.add_argument('--classes', type=str,default='model_data/key_classes.txt',
help='path to class definitions, default '
+ YOLO.get_defaults('classes_path'))
parser.add_argument('--gpu_num', type=int,
help='Number of GPU to use, default '
+ str(YOLO.get_defaults('gpu_num')))
parser.add_argument('--image', default=False, action='store_true',
help='Image detection mode, will ignore all positional arguments'
def main():
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(
argument_default=argparse.SUPPRESS,
description=
'Demo of multi object tracking (MOT) with YOLO detection model')
'''
MOT model options
'''
parser.add_argument(
'--tracking_model_type',
type=str,
default="sort",
choices=['sort', 'deepsort'],
help="MOT model type (sort/deepsort), default=%(default)s")
parser.add_argument(
'--tracking_classes_path',
type=str,
required=False,
help=
'[Optional] Path to DeepSORT tracking class definitions, will track all detect classes if None, default=%(default)s',
default=None)
parser.add_argument(
'--deepsort_model_path',
type=str,
required=False,
default="tracking/model/mars-small128.pb",
help="[Optional] DeepSORT encoder model path, default=%(default)s")
'''
YOLO model options
'''
parser.add_argument(
'--model_type',
type=str,
help=
'YOLO model type: yolo3_mobilenet_lite/tiny_yolo3_mobilenet/yolo3_darknet/..., default '
+ YOLO.get_defaults("model_type"))
parser.add_argument('--weights_path',
type=str,
help='path to YOLO model weight file, default ' +
YOLO.get_defaults("weights_path"))
parser.add_argument(
'--pruning_model',
default=False,
action="store_true",
help='Whether using a pruning YOLO model/weights file, default ' +
str(YOLO.get_defaults("pruning_model")))
parser.add_argument('--anchors_path',
type=str,
help='path to YOLO anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument(
'--classes_path',
type=str,
help='path to YOLO detection class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument(
'--model_image_size',
type=str,
help='YOLO detection model input size as <height>x<width>, default ' +
str(YOLO.get_defaults("model_image_size")[0]) + 'x' +
str(YOLO.get_defaults("model_image_size")[1]),
default=str(YOLO.get_defaults("model_image_size")[0]) + 'x' +
str(YOLO.get_defaults("model_image_size")[1]))
parser.add_argument(
'--score',
type=float,
help='score threshold for YOLO detection model, default ' +
str(YOLO.get_defaults("score")))
parser.add_argument('--iou',
type=float,
help='iou threshold for YOLO detection NMS, default ' +
str(YOLO.get_defaults("iou")))
parser.add_argument(
'--elim_grid_sense',
default=False,
action="store_true",
help="Whether to apply eliminate grid sensitivity in YOLO, default " +
str(YOLO.get_defaults("elim_grid_sense")))
#parser.add_argument(
#'--gpu_num', type=int,
#help='Number of GPU to use, default ' + str(YOLO.get_defaults("gpu_num"))
#)
'''
Command line positional arguments -- for video detection mode
'''
parser.add_argument("--input",
nargs='?',
type=str,
required=False,
default='./path2your_video',
help="Input video file or images folder path")
parser.add_argument("--output",
nargs='?',
type=str,
default="",
help="[Optional] output video file path")
args = parser.parse_args()
# param parse
if args.model_image_size:
height, width = args.model_image_size.split('x')
args.model_image_size = (int(height), int(width))
assert (args.model_image_size[0] % 32 == 0
and args.model_image_size[1] % 32
== 0), 'model_image_size should be multiples of 32'
# get YOLO wrapped detection object
yolo = YOLO_np(**vars(args))
# choose different MOT model
if args.tracking_model_type == 'sort':
sort(yolo, args)
elif args.tracking_model_type == 'deepsort':
deepsort(yolo, args)
else:
raise ValueError('Unsupported MOT model')
save_file_Path = pathlib.Path("./out") / filepath[len(images_dirpath)+1:]
save_file_Path.parent.mkdir(mode=0o755, parents=True, exist_ok=True)
r_image.save(str(save_file_Path), "JPEG")
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
'--model_path', type=str,
help='path to model weight file, default ' + YOLO.get_defaults("model_path")
)
parser.add_argument(
'--anchors_path', type=str,
help='path to anchor definitions, default ' + YOLO.get_defaults("anchors_path")
)
parser.add_argument(
'--classes_path', type=str,
help='path to class definitions, default ' + YOLO.get_defaults("classes_path")
)
parser.add_argument(
'--gpu_num', type=int,
help='Number of GPU to use, default ' + str(YOLO.get_defaults("gpu_num"))
else:
r_image = yolo.detect_image(image)
r_image.show()
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
'--model', type=str,
help='path to model weight file, default ' + YOLO.get_defaults("/content/gdrive/My Drive/project_folder/keras-yolo3/model_data/yolo.h5")
)
parser.add_argument(
'--anchors', type=str,
help='path to anchor definitions, default ' + YOLO.get_defaults("/content/gdrive/My Drive/project_folder/keras-yolo3/model_data/yolo_anchors.txt")
)
parser.add_argument(
'--classes', type=str,
help='path to class definitions, default ' + YOLO.get_defaults("/content/gdrive/My Drive/project_folder/keras-yolo3/model_data/coco_classes.txt")
)
parser.add_argument(
'--gpu_num', type=int,
help='Number of GPU to use, default ' + str(YOLO.get_defaults("gpu_num"))
def start(path, file_extension, code):
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
'--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_data/model1-tiny_last_weights.h5"))
parser.add_argument('--anchors',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("tiny_yolo_anchors.txt"))
parser.add_argument('--classes',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("coco_classes.txt"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
parser.add_argument(
'--image',
default=False,
action="store_true",
help='Image detection mode, will ignore all positional arguments')
'''
Command line positional arguments -- for video detection mode
'''
parser.add_argument("--input",
nargs='?',
type=str,
required=False,
default=path,
help="Video input path")
parser.add_argument("--output",
nargs='?',
type=str,
default="./output",
help="[Optional] Video output path")
FLAGS = parser.parse_args()
#print(FLAGS.input.shape)
if file_extension == ".jpg" or file_extension == ".png" or file_extension == ".jpeg" or file_extension == ".JPG" or file_extension == ".JPEG":
"""
Image detection mode, disregard any remaining command line arguments
"""
print("Image detection mode")
print('img\nimg\nimg\nimg\nimg\nimg\nimg\nimg\nimg\n')
print(" Ignoring remaining command line arguments: " + FLAGS.input +
"," + FLAGS.output)
path_img, predicted_class, score_list, gesture, gesture_score = detect_img(
YOLO(**vars(FLAGS)), path, code)
return path_img, predicted_class, score_list, gesture, gesture_score
elif "input" in FLAGS:
print(FLAGS.input, 'vid\nvid\nvid\nvid\nvid\nvid\nvid\nvid\nvid\n')
detect_video(YOLO(**vars(FLAGS)), FLAGS.input, FLAGS.output)
else:
print(
"Must specify at least video_input_path. See usage with --help.")
for f in os.listdir('all_detections'):
os.remove(os.path.join('all_detections', f))
#for f in os.listdir('violations'):
#os.remove(os.path.join('violations',f))
for f in os.listdir('helmet_detections'):
os.remove(os.path.join('helmet_detections', f))
'''
Command line options
'''
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument('--classes',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
print('Open Error! Try again!')
continue
else:
r_image = yolo.detect_image(image)
r_image.show()
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
FLAGS = {
'model': "./model_data/yolo.h5",
'anchors': YOLO.get_defaults("anchors_paths"),
'classes': YOLO.get_defaults("classes_path"),
'gpu_num': YOLO.get_defaults("gpu_num"),
'image': False,
'input': "./data/visor_video.wmv",
'output': "./video_output.wmv"
}
if FLAGS['image']:
"""
Image detection mode, disregard any remaining command line arguments
"""
print("Image detection mode")
if "input" in FLAGS:
print(" Ignoring remaining command line arguments: " +
FLAGS['input'] + "," + FLAGS['output'])
def parse_args():
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
parser.add_argument('--model_path',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors_path',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument('--classes_path',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
parser.add_argument('--score',
type=float,
help='Score to use, default ' +
str(YOLO.get_defaults("score")))
parser.add_argument('--input_path',
nargs='?',
type=str,
required=True,
default='',
help='Input dataset path')
parser.add_argument('--output_path',
nargs='?',
type=str,
required=True,
default='',
help='Output dataset path')
parser.add_argument('--class_name',
nargs='?',
type=str,
required=True,
default='',
help='Name of the class used to create dataset')
parser.add_argument('--width',
nargs='?',
type=int,
required=True,
help='With of the output images')
parser.add_argument('--height',
nargs='?',
type=int,
required=True,
help='Height of the output images')
return parser.parse_args()
]
if box_strings:
print(' '.join(box_strings))
print('\n')
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--score',
type=float,
help='score (confidence) threshold, default ' +
str(YOLO.get_defaults("score")))
parser.add_argument('--shuffle',
default=False,
action="store_true",
help='shuffle images for display mode')
parser.add_argument(
'--display',
default=False,
action="store_true",
else:
r_image = yolo.detect_image(image)
r_image.show()
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
'--model', type=str,
help='path to model weight file, default ' + YOLO.get_defaults("model_path")
)
parser.add_argument(
'--anchors', type=str,
help='path to anchor definitions, default ' + YOLO.get_defaults("anchors_path")
)
parser.add_argument(
'--classes', type=str,
help='path to class definitions, default ' + YOLO.get_defaults("classes_path")
)
parser.add_argument(
'--gpu_num', type=int,
help='Number of GPU to use, default ' + str(YOLO.get_defaults("gpu_num"))
from PIL import Image
import cv2
def detect_img(yolo):
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
r_image = yolo.detect_image(image)
r_image.show()
# r_image.save("./result.jpg")
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
YOLO.get_defaults("model_path")
YOLO.get_defaults("anchors_path")
YOLO.get_defaults("classes_path")
yolo = YOLO(model_path="./logs/000/ep024-loss46.727-val_loss42.751.h5",
classes_path="./model_data/danger.txt")
detect_img(yolo)
from yolo import YOLO, detect_video
from PIL import Image
import pdb
def detect_img(yolo):
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
r_image = yolo.detect_image(image)
r_image.show()
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_path',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"),
default='model_data/trained_weights_final.h5')
FLAGS = parser.parse_args()
detect_img(YOLO(**vars(FLAGS)))
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
parser.add_argument(
'--model',
type=str,
default='weights_yolo_train/trained_weights_stage_1.h5',
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors',
type=str,
default='model_data/yolo_anchors.txt',
help='path to anchor definitions, default ' +
YOLO.get_defaults('anchors_path'))
parser.add_argument('--classes',
type=str,
default='model_data/key_classes.txt',
help='path to class definitions, default ' +
YOLO.get_defaults('classes_path'))
parser.add_argument('--gpu_num',
type=int,
def instantiate():
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument('--classes',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
parser.add_argument(
'--image',
default=False,
action="store_true",
help='Image detection mode, will ignore all positional arguments')
'''
Command line positional arguments -- for video detection mode
'''
parser.add_argument("--input",
nargs='?',
type=str,
required=False,
default='./path2your_video',
help="Video input path")
parser.add_argument("--output",
nargs='?',
type=str,
default="",
help="[Optional] Video output path")
FLAGS = parser.parse_args()
if FLAGS.image:
"""
Image detection mode, disregard any remaining command line arguments
"""
print("Image detection mode")
if "input" in FLAGS:
print(" Ignoring remaining command line arguments: " +
FLAGS.input + "," + FLAGS.output)
detect_img(YOLO(**vars(FLAGS)))
elif "input" in FLAGS:
detect_video(YOLO(**vars(FLAGS)), FLAGS.input, FLAGS.output)
else:
print(
"Must specify at least video_input_path. See usage with --help.")
r_image.show()
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument('--model',
type=str,
help='path to model weight file, default ' +
YOLO.get_defaults("model_path"))
parser.add_argument('--anchors',
type=str,
help='path to anchor definitions, default ' +
YOLO.get_defaults("anchors_path"))
parser.add_argument('--classes',
type=str,
help='path to class definitions, default ' +
YOLO.get_defaults("classes_path"))
parser.add_argument('--gpu_num',
type=int,
help='Number of GPU to use, default ' +
str(YOLO.get_defaults("gpu_num")))
# r_image.show()
opencvImage = cv2.cvtColor(numpy.array(image), cv2.COLOR_RGB2BGR)
cv2.imwrite('pictures/test_result.png',opencvImage)
yolo.close_session()
FLAGS = None
if __name__ == '__main__':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
'--model_path', type=str,
help='path to model weight file, default ' + YOLO.get_defaults("model_path")
)
parser.add_argument(
'--anchors', type=str,
help='path to anchor definitions, default ' + YOLO.get_defaults("anchors_path")
)
parser.add_argument(
'--classes_path', type=str,
help='path to class definitions, default ' + YOLO.get_defaults("classes_path")
)
parser.add_argument(
'--gpu_num', default=1, type=int,
help='Number of GPU to use, default 1 '
