def convert_file(net, filename, output, cfg):
assert os.path.isfile(
filename), 'Please provide a path to an existing image!'
pyramid = True if len(cfg.TEST.SCALES) > 1 else False
cls_dets, _ = detect(net,
filename,
visualization_folder=output,
visualize=True,
pyramid=pyramid)
if args.cfg is not None:
cfg_from_file(args.cfg)
# Print config file
cfg_print(cfg)
# Loading the network
cfg.GPU_ID = args.gpu_id
caffe.set_mode_gpu()
caffe.set_device(args.gpu_id)
assert os.path.isfile(
args.prototxt), 'Please provide a valid path for the prototxt!'
assert os.path.isfile(
args.model), 'Please provide a valid path for the caffemodel!'
print('Loading the network...', end="")
net = caffe.Net(args.prototxt, args.model, caffe.TEST)
net.name = 'SSH'
print('Done!')
# Read image
assert os.path.isfile(
args.im_path), 'Please provide a path to an existing image!'
pyramid = True if len(cfg.TEST.SCALES) > 1 else False
# Perform detection
cls_dets, _ = detect(net,
args.im_path,
visualization_folder=args.out_path,
visualize=True,
pyramid=pyramid)
# Load the external config
if args.cfg is not None:
cfg_from_file(args.cfg)
# Print config file
cfg_print(cfg)
# Loading the network
cfg.GPU_ID = args.gpu_id
caffe.set_mode_gpu()
caffe.set_device(args.gpu_id)
assert os.path.isfile(args.prototxt),'Please provide a valid path for the prototxt!'
assert os.path.isfile(args.model),'Please provide a valid path for the caffemodel!'
print('Loading the network...', end="")
net = caffe.Net(args.prototxt, args.model, caffe.TEST)
net.name = 'SSH'
print('Done!')
# Read image
assert os.path.isfile(args.im_path),'Please provide a path to an existing image!'
pyramid = True if len(cfg.TEST.SCALES)>1 else False
# Perform detection
cls_dets,_ = detect(net,args.im_path,visualization_folder=args.out_path,visualize=True,pyramid=pyramid)
assert os.path.exists(
args.trudir), 'Please provide a valid path for ground truth dir'
alltrueface = 0
alldetectface = 0
alldetectfaceright = 0
start = time.time()
#processing start
for imgfile in os.listdir(args.imdir):
# Face cut list
images = []
groundtruth = []
im = cv2.imread(os.path.join(args.imdir, imgfile))
print('Detecting File {0}'.format(imgfile))
cls_dets, _ = detect(net,
im,
visualization_folder=args.out_path,
visualize=False,
pyramid=pyramid)
xmlfile = os.path.join(args.trudir, (imgfile.split('.')[0] + '.xml'))
tree = ET.parse(xmlfile)
root = tree.getroot()
for obj in root.findall('object'):
objname = obj.find('name').text
bbox = obj.find('bndbox')
xmin = int(bbox.find('xmin').text)
xmax = int(bbox.find('xmax').text)
ymin = int(bbox.find('ymin').text)
ymax = int(bbox.find('ymax').text)
groundtruth.append((objname, [xmin, xmax, ymin, ymax]))
'''
#visulize detection results