def text_detect(text_detector, image_path, img_type):
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Image: %s"%image_path
if img_type == "others":
return [],0
im=cv2.imread(image_path)
im_small, f=resize_im(im, Config.SCALE, Config.MAX_SCALE)
timer = Timer()
timer.tic()
text_lines = text_detector.detect(im_small)
text_lines = text_lines / f # project back to size of original image
text_lines = refine_boxes(im, text_lines, expand_pixel_len = Config.DILATE_PIXEL,
pixel_blank = Config.BREATH_PIXEL, binary_thresh=Config.BINARY_THRESH)
text_area_ratio = calc_area_ratio(text_lines, im.shape)
print "Number of the detected text lines: %s" % len(text_lines)
print "Detection Time: %f" % timer.toc()
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
if Config.DEBUG_SAVE_BOX_IMG:
im_with_text_lines = draw_boxes(im, text_lines, is_display=False, caption=image_path, wait=False)
if im_with_text_lines is not None:
cv2.imwrite(image_path+'_boxes.jpg', im_with_text_lines)
return text_lines, text_area_ratio
def text_detect(args, text_detector, image_path):
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Image: %s" % image_path
im = cv2.imread(image_path)
im_small, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
timer = Timer()
timer.tic()
text_lines = text_detector.detect(im_small)
text_lines = text_lines / f # project back to size of original image
text_lines = refine_boxes(im, text_lines)
text_lines = rank_boxes(text_lines)
print "Number of the detected text lines: %s" % len(text_lines)
print "Detection Time: %f" % timer.toc()
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
if args.SAVE_IMAGE_WITH_BOX:
im_with_text_lines = draw_boxes(im,
text_lines,
is_display=False,
caption=image_path,
wait=False)
if im_with_text_lines is not None:
cv2.imwrite(image_path + '_boxes.jpg', im_with_text_lines)
return im, text_lines
def detect(root, img_file, model_file):
net = Net.CTPN()
net.load_state_dict(torch.load(model_file))
# net.cuda()
print(net)
net.eval()
text_connector = TextProposalConnector()
im = cv2.imread(os.path.join(root, img_file))
# im = Dataset.scale_img(im, None, shortest_side=600)
img = copy.deepcopy(im)
img = img.transpose(2, 0, 1)
img = img[np.newaxis, :, :, :]
img = torch.Tensor(img)
# img = img.cuda()
v, score, side = net(img, val=True)
score = score.cpu().detach().numpy()[:, :, :, 1]
result = np.where(score > 0.7)
for_nms = []
for anchor, height, width in zip(result[0], result[1], result[2]):
vc = v[anchor, 0, height, width]
vh = v[anchor, 1, height, width]
cya = height * 16 + 7.5
ha = anchor_height[anchor]
cy = vc * ha + cya
h = math.pow(10, vh) * ha
pt = other.trans_to_2pt(width, cy, h)
for_nms.append(
[pt[0], pt[1], pt[2], pt[3], score[anchor, height, width]])
for_nms = np.array(for_nms, dtype=np.float32)
nms_result = nms.cpu_nms(for_nms, TEXT_LINE_NMS_THRESH)
text_proposals = []
text_proposal_score = []
for i in nms_result:
text_proposals.append(for_nms[i, 0:4])
text_proposal_score.append(for_nms[i, 4])
text_proposals = np.array(text_proposals)
text_proposal_score = np.array(text_proposal_score)
text_proposal_score = other.normalize(text_proposal_score)
text_lines = text_connector.get_text_lines(text_proposals,
text_proposal_score,
im.shape[:2])
keep_index = filter_boxes(text_lines)
text_lines = text_lines[keep_index]
# nms for text lines
if text_lines.shape[0] != 0:
keep_inds = nms.cpu_nms(text_lines, TEXT_LINE_NMS_THRESH)
text_lines = text_lines[keep_inds]
rec = other.draw_boxes(im, text_lines)
rec_file = open(os.path.join(img_dir,
img_file.split('.')[0] + '.txt'), 'w')
rec = rec.tolist()
for box in rec:
box = [str(pt) for pt in box]
rec_file.write(','.join(box))
rec_file.write('\n')
def getTextRec(text_detector, im):
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
#generator the copy
tmp = im.copy()
text_lines = text_detector.detect(im)
imsrc, text_recs = draw_boxes(tmp,
text_lines,
caption='im_name',
wait=True)
return tmp, imsrc, text_recs
def getCharBlock(text_detector, im):
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
tmp = im.copy()
#timer=Timer()
#timer.tic()
text_lines = text_detector.detect(im)
#print "Number of the detected text lines: %s"%len(text_lines)
#print "Time: %f"%timer.toc()
text_recs = draw_boxes(tmp, text_lines, caption='im_name', wait=True)
return tmp, text_recs
def getCharBlock(text_detector,im):
im, f=resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
cv2.imshow("src", im)
tmp = im.copy()
#timer=Timer()
#timer.tic()
text_lines=text_detector.detect(im)
#print "Number of the detected text lines: %s"%len(text_lines)
#print "Time: %f"%timer.toc()
text_recs = draw_boxes(tmp, text_lines, caption='im_name', wait=True)
return tmp,text_recs
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector = TextDetector(text_proposals_detector)
demo_imnames = os.listdir(DEMO_IMAGE_DIR)
timer = Timer()
for im_name in demo_imnames:
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Image: %s" % im_name
im_file = osp.join(DEMO_IMAGE_DIR, im_name)
im = cv2.imread(im_file)
timer.tic()
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines = text_detector.detect(im)
print "Number of the detected text lines: %s" % len(text_lines)
print "Time: %f" % timer.toc()
im_with_text_lines = draw_boxes(im,
text_lines,
caption=im_name,
wait=False)
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Thank you for trying our demo. Press any key to exit..."
cv2.waitKey(0)
text_detector = TextDetector(text_proposals_detector)
demo_imnames = os.listdir(DEMO_IMAGE_DIR)
timer = Timer()
for im_name in demo_imnames:
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Image: %s" % im_name
im_file = osp.join(DEMO_IMAGE_DIR, im_name)
im = cv2.imread(im_file)
timer.tic()
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines = text_detector.detect(im)
print "Number of the detected text lines: %s" % len(text_lines)
print "Time: %f" % timer.toc()
im_with_text_lines = draw_boxes(im,
text_lines,
is_display=False,
caption=im_name,
wait=False)
cv2.imwrite("%s_res.jpg" % im_name[:-4], im_with_text_lines)
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Thank you for trying our demo. Press any key to exit..."
cv2.waitKey(0)
timer=Timer()
for im_name in demo_imnames:
print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
print("Image: %s"%im_name)
im_file=osp.join(DEMO_IMAGE_DIR, im_name)
im=cv2.imread(im_file)
timer.tic()
im, f=resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines=text_detector.detect(im)
print("Number of the detected text lines: %s"%len(text_lines))
print("Time: %f"%timer.toc())
im_with_text_lines=draw_boxes(
im, text_lines,
is_display=IS_CV_DISPLAY,
caption=im_name,
wait=False)
if not IS_CV_DISPLAY:
cv2.imwrite(f'{args.output_dir}/output_{im_name}', im_with_text_lines)
print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
if IS_CV_DISPLAY:
print("Thank you for trying our demo. Press any key to exit...")
cv2.waitKey(0)
path = os.path.abspath(os.curdir)
timer=Timer()
print("\ninput exit break\n")
while 1 :
if sys.version_info >= (3, 0):
im_name = input("\nplease input file name:")
else:
im_name = raw_input("\nplease input file name:")
if im_name == "exit":
break
im_path = path + "/../img/" + im_name
im = cv2.imread(im_path)
if im is None:
continue
im, f=resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
cv2.imshow("src", im)
tmp = im.copy()
timer.tic()
text_lines=text_detector.detect(im)
print("Number of the detected text lines: %s"%len(text_lines))
print("Time: %f"%timer.toc())
im_with_text_lines=draw_boxes(tmp, text_lines, caption=im_name, wait=True)
text_proposals_detector = TextProposalDetector(CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector = TextDetector(text_proposals_detector)
path = os.path.abspath(os.curdir)
timer=Timer()
print "\ninput exit break\n"
while 1 :
im_name = raw_input("\nplease input file name:")
if im_name == "exit":
break
im_path = path + "/demo_images/" + im_name
im = cv2.imread(im_path)
if im is None:
continue
im, f=resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
cv2.imshow("src", im)
tmp = im.copy()
timer.tic()
text_lines=text_detector.detect(im)
print "Number of the detected text lines: %s"%len(text_lines)
print "Time: %f"%timer.toc()
im_with_text_lines=draw_boxes(tmp, text_lines, caption=im_name, wait=True)
caffe.set_device(cfg.TEST_GPU_ID)
# initialize the detectors
text_proposals_detector=TextProposalDetector(CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector=TextDetector(text_proposals_detector)
demo_imnames=os.listdir(DEMO_IMAGE_DIR)
timer=Timer()
for im_name in demo_imnames:
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Image: %s"%im_name
im_file=osp.join(DEMO_IMAGE_DIR, im_name)
im=cv2.imread(im_file)
timer.tic()
im, f=resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines=text_detector.detect(im)
print "Number of the detected text lines: %s"%len(text_lines)
print "Time: %f"%timer.toc()
im_with_text_lines=draw_boxes(im, text_lines, caption=im_name, wait=False)
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "Thank you for trying our demo. Press any key to exit..."
cv2.waitKey(0)
exit()
# initialize the detectors
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector = TextDetector(text_proposals_detector)
timer = Timer()
cam = cv2.VideoCapture(vid)
while True:
ret, im = cam.read()
if not ret:
break
timer.tic()
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines = text_detector.detect(im)
print "Number of the detected text lines: %s" % len(text_lines)
print "Time: %f" % timer.toc()
im_with_text_lines = draw_boxes(im,
text_lines,
caption="Text Detection",
wait=False)
key = cv2.waitKey(1)
if key == 27:
break
