def prepareImage(imagePath):
""" Prepare images before use it.
"""
print("> Prepare image "+imagePath + ":")
imname = ntpath.basename(imagePath)
imname = imname.split(imname.split('.')[-1])[0][0:-1] # 记录图片basename
img = cv2.imread( imagePath ) # 加载图片
if needCrop:
dlib_img = io.imread(imagePath)
img2 = cv2.copyMakeBorder(img,0,0,0,0,cv2.BORDER_REPLICATE)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(FLAGS.predictor_path) # 加载 dlib 检测
dets = detector(img, 1)
print("> Number of faces detected: {}".format(len(dets)))
if len(dets) == 0:
print '> Could not detect the face, skipping the image...' + image_path
return None
if len(dets) > 1:
print "> Process only the first detected face!"
# 标记第一个人脸
detected_face = dets[0]
cv2.rectangle(img2, (detected_face.left(),detected_face.top()), \
(detected_face.right(),detected_face.bottom()), (0,0,255),2)
fileout = open(os.path.join(FLAGS.tmp_detect , imname + ".bbox"),"w")
fileout.write("%f %f %f %f\n" % (detected_face.left(),detected_face.top(), \
detected_face.right(),detected_face.bottom()))
fileout.close()
## If we are using landmarks to crop
if useLM:
shape = predictor(dlib_img, detected_face)
nLM = shape.num_parts
fileout = open(os.path.join(FLAGS.tmp_detect, imname + ".pts" ), "w")
for i in range(0, nLM):
cv2.circle( img2, (shape.part(i).x, shape.part(i).y), 5, (255,0,0))
fileout.write("%f %f\n" % (shape.part(i).x, shape.part(i).y))
fileout.close()
img = utils.cropByLM(img, shape, img2)
else:
print "> cropByFaceDet "
img = utils.cropByFaceDet(img, detected_face, img2)
cv2.imwrite(os.path.join( FLAGS.tmp_detect, imname+"_detect.png"), img2)
img = cv2.resize(img, (trg_size, trg_size))
cv2.imwrite(os.path.join(FLAGS.tmp_ims, imname + '.png'), img)
return img
fileout.write("%f %f %f %f\n" % (detected_face.left(),detected_face.top(), \
detected_face.right(),detected_face.bottom()))
fileout.close()
## If we are using landmarks to crop
if useLM:
shape = predictor(dlib_img, detected_face)
nLM = shape.num_parts
fileout = open("tmp_detect/"+imname+".pts","w")
for i in range(0,nLM):
cv2.circle(img2, (shape.part(i).x, shape.part(i).y), 5, (255,0,0))
fileout.write("%f %f\n" % (shape.part(i).x, shape.part(i).y))
fileout.close()
img = utils.cropByLM(img, shape, img2)
else:
print "> cropByFaceDet "
img = utils.cropByFaceDet(img, detected_face, img2)
cv2.imwrite("tmp_detect/"+imname+"_detect.png",img2)
img = cv2.resize(img,(trg_size, trg_size))
cv2.imwrite("tmp_ims/" + imname + ".png",img)
#####CNN fitting ##############################
start_time = time.time()
# load net
try:
caffe.set_mode_gpu()
caffe.set_device(GPU_ID)
except Exception as ex:
print '> Could not setup Caffe in GPU ' +str(GPU_ID) + ' - Error: ' + ex
print '> Reverting into CPU mode'
caffe.set_mode_cpu()