def textPredict(input_path):
#CPU mode setting
if len(sys.argv)>1 and sys.argv[1]=="--no-gpu":
caffe.set_mode_cpu()
else:
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
model_path = "../models/"
# initialize the detectors
NET_DEF_FILE = model_path + "deploy.prototxt"
MODEL_FILE = model_path + "ctpn_trained_model.caffemodel"
text_proposals_detector=TextProposalDetector(CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector=TextDetector(text_proposals_detector)
im=cv2.imread(input_path)
#h = im.shape[0]
#w = im.shape[1]
im, f=resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines=text_detector.detect(im)
return text_lines,f
def detect_text_boxes(video_pk, cpu_mode=False):
"""
Detect Text Boxes in frames for a video using CTPN, must be run in dva_ctpn container
:param detector_pk
:param video_pk
:return:
"""
setup_django()
from dvaapp.models import Region, Frame
from django.conf import settings
from PIL import Image
import sys
video_pk = int(video_pk)
sys.path.append('/opt/ctpn/CTPN/tools/')
sys.path.append('/opt/ctpn/CTPN/src/')
from cfg import Config as cfg
from other import resize_im, CaffeModel
import cv2, caffe
from detectors import TextProposalDetector, TextDetector
NET_DEF_FILE = "/opt/ctpn/CTPN/models/deploy.prototxt"
MODEL_FILE = "/opt/ctpn/CTPN/models/ctpn_trained_model.caffemodel"
if cpu_mode: # Set this to true for CPU only mode
caffe.set_mode_cpu()
else:
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector = TextDetector(text_proposals_detector)
for f in Frame.objects.all().filter(video_id=video_pk):
path = "{}/{}/frames/{}.jpg".format(settings.MEDIA_ROOT, video_pk,
f.frame_index)
im = cv2.imread(path)
old_h, old_w, channels = im.shape
im, _ = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
new_h, new_w, channels = im.shape
mul_h = float(old_h) / float(new_h)
mul_w = float(old_w) / float(new_w)
text_lines = text_detector.detect(im)
for k in text_lines:
left, top, right, bottom, score = k
left, top, right, bottom = int(left * mul_w), int(
top * mul_h), int(right * mul_w), int(bottom * mul_h)
r = Region()
r.region_type = r.DETECTION
r.confidence = int(100.0 * score)
r.object_name = "CTPN_TEXTBOX"
r.y = top
r.x = left
r.w = right - left
r.h = bottom - top
r.frame_id = f.pk
r.video_id = video_pk
r.save()
right = r.w + r.x
bottom = r.h + r.y
img = Image.open(path)
img2 = img.crop((left, top, right, bottom))
img2.save("{}/{}/detections/{}.jpg".format(settings.MEDIA_ROOT,
video_pk, r.pk))
def __init__(self, mode):
if mode == "GPU":
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
else:
caffe.set_mode_cpu()
netfile = cfg.NET_FILE
modelfile = cfg.MODEL_FILE
# initialize the detectors
self.text_proposals_detector = TextProposalDetector(
CaffeModel(netfile, modelfile))
self.text_detector = TextDetector(self.text_proposals_detector)
self.timer = Timer()
self.char_classifier = caffe.Classifier(
cfg.FONT_PROTO,
cfg.FONT_MODEL,
mean=np.load(cfg.FONT_MEANFILE).mean(1).mean(1),
channel_swap=(2, 1, 0),
raw_scale=255,
image_dims=(cfg.FONT_DIMS, cfg.FONT_DIMS))
with open(cfg.FONT_LBLFILE, 'r') as f:
self.fontLabels = [x.strip() for x in f]
def init(model_file, trained_file):
# initialize the detectors
global text_proposals_detector
global text_detector
caffe_model = CaffeModel(model_file, trained_file)
text_proposals_detector = TextProposalDetector(caffe_model)
text_detector = TextDetector(text_proposals_detector)
def get_text_lines(self, im, NET_DEF_FILE, MODEL_FILE):
# initialize the detectors
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
text_detector = TextDetector(text_proposals_detector)
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines = text_detector.detect(im)
return text_lines / f
def load(self):
logging.info('Creating networks and loading parameters')
NET_DEF_FILE = "/opt/ctpn/CTPN/models/deploy.prototxt"
MODEL_FILE = "/opt/ctpn/CTPN/models/ctpn_trained_model.caffemodel"
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
self.session = TextDetector(text_proposals_detector)
def ctpnSource():
DEMO_IMAGE_DIR = "img/"
NET_DEF_FILE = "CTPN/models/deploy.prototxt"
MODEL_FILE = "CTPN/models/ctpn_trained_model.caffemodel"
caffe.set_mode_gpu()
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)
return text_detector
def __init__(self):
'''
@Construction for text detector.
This class initiates the constructor for
'''
self.NET_DEF_FILE = "models/deploy.prototxt"
self.MODEL_FILE = "models/ctpn_trained_model.caffemodel"
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
self.text_proposals_detector = TextProposalDetector(CaffeModel(self.NET_DEF_FILE, self.MODEL_FILE))
self.text_detector = TextDetector(self.text_proposals_detector)
def init_models(args):
if cfg.PLATFORM == "GPU":
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
else:
caffe.set_mode_cpu()
# initialize the detectors
text_proposals_detector=TextProposalDetector(CaffeModel(args.DET_NET_DEF_FILE, args.DET_MODEL_FILE))
text_detector=TextDetector(text_proposals_detector)
return text_detector
def load(self):
logging.info('Creating networks and loading parameters')
if os.environ.get('GPU_AVAILABLE', False):
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
logging.info("GPU mode")
else:
caffe.set_mode_cpu()
logging.info("CPU mode")
text_proposals_detector = TextProposalDetector(
CaffeModel(self.network_def, self.model_path))
self.session = TextDetector(text_proposals_detector)
logging.info('model loaded!')
def __init__(self, dir_model, gpu_id):
NET_DEF_FILE = dir_model + "/bib_number/CTPN/deploy.prototxt"
MODEL_FILE = dir_model + "/bib_number/CTPN/ctpn_trained_model.caffemodel"
if False: # Set this to true for CPU only mode
caffe.set_mode_cpu()
else:
caffe.set_mode_gpu()
caffe.set_device(int(gpu_id)) # (cfg.TEST_GPU_ID)
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
self.text_detector = TextDetector(text_proposals_detector)
length_regexp = 'Duration: (\d{2}):(\d{2}):(\d{2})\.\d+,'
self.re_length = re.compile(length_regexp)
def ctpnSource():
DEMO_IMAGE_DIR = "img/"
# net类
NET_DEF_FILE = "CTPN/models/deploy.prototxt"
# 训练好的模型文件
MODEL_FILE = "CTPN/models/ctpn_trained_model.caffemodel"
caffe.set_mode_gpu()
caffe.set_device(cfg.TEST_GPU_ID)
# initialize the detectors
# 初步的proposal检测器类
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
# 进一步的（含文本线构造器）检测器类
text_detector = TextDetector(text_proposals_detector)
return text_detector
def text_detec(img_url):
caffe.set_mode_gpu()
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)
im = cv2.imread(img_url)
timer.tic()
im, f = resize_im(im, cfg.SCALE, cfg.MAX_SCALE)
text_lines = text_detector.detect(im)
obj_num = len(text_lines)
print "Number of the detected text lines: %s" % len(text_lines)
print "Time: %f" % timer.toc()
boxstr = u''
count = 0
#http://192.168.7.37:8393/static/jz66f1d49d97d048fe9e4a62004199d0b2_1_for_trail.jpg
print text_lines
for bbox in text_lines:
print bbox
count += 1
boxstr += "text[%d]:[%f,%f,%f,%f]<br/>" % (count, bbox[0], bbox[1],
bbox[2], bbox[3])
im_name = img_url.split('/')[-1]
im_name.replace("?", '_')
im_name.replace("%", '_')
im_name.replace("&", '_')
im_name.replace("=", '_')
local_url = img_url
write_path = "/data1/mingmingzhao/data_sets/test/text_detect/text_detect_%s" % (
local_url.split('/')[-1])
print "write_path:" + write_path
im_with_text_lines = draw_boxes_zmm(im,
text_lines,
caption=write_path,
wait=False)
server_url = "http://192.168.7.37:8393/static/text_detect/%s" % (
write_path.split('/')[-1])
print "server_url:" + server_url
return boxstr, server_url, count
def __init__(self, NET_DEF_FILE, MODEL_FILE, caffe_path):
sys.path.insert(0, "%s/python" % caffe_path)
import caffe
from other import draw_boxes, resize_im, CaffeModel
from detectors import TextProposalDetector, TextDetector
sys.path.remove("%s/python" % caffe_path)
#def ctpnSource(NET_DEF_FILE, MODEL_FILE, use_gpu):
#NET_DEF_FILE = "CTPN/models/deploy.prototxt"
#MODEL_FILE = "CTPN/models/ctpn_trained_model.caffemodel"
self.caffe = caffe
#if use_gpu:
# caffe.set_mode_gpu()
# caffe.set_device(cfg.TEST_GPU_ID)
#else:
# caffe.set_mode_cpu()
# initialize the detectors
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
self.text_detector = TextDetector(text_proposals_detector)
self.resize_im = resize_im
self.draw_boxes = draw_boxes
from detectors import TextProposalDetector, TextDetector
import os.path as osp
from ctpn_utils.timer import Timer
DEMO_IMAGE_DIR = "demo_images/"
NET_DEF_FILE = "models/deploy.prototxt"
MODEL_FILE = "models/ctpn_trained_model.caffemodel"
if len(sys.argv) > 1 and sys.argv[1] == "--no-gpu":
caffe.set_mode_cpu()
else:
caffe.set_mode_gpu()
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)
def load_model(self):
caffe.set_mode_cpu()
text_proposals_detector = TextProposalDetector(
CaffeModel(NET_DEF_FILE, MODEL_FILE))
self.text_detector = TextDetector(text_proposals_detector)
