def get_rectangle_indiviual(image_id, number):
name = get_face_image_name(image_id, type="rect", full_path=False)
save_path = fm.get_save_path(image_id)
res = circumscribe_face(save_path, name[5:], save_path, int(number))
fullpath = save_path + "/" + name
with open(fullpath) as f:
image = f.read()
content_type = fm.get_content_type(fullpath)
return put_response(image, content_type=content_type)
def get_rectangle_indiviual(image_id, number):
name = get_face_image_name(image_id, type="rect", full_path=False)
save_path = filemanager.get_save_path(image_id)
res = circumscribe_face(save_path, name[5:], save_path, int(number))
fullpath = save_path + "/" + name;
with open(fullpath) as f:
image = f.read()
content_type = filemanager.get_content_type(fullpath)
return put_response(image, content_type=content_type)
def upload_file():
files = request.files
res = filemanager.upload_file(files)
if res["status"] == "success":
name = res["detail"]["name"]
id = res["detail"]["id"]
save_path = filemanager.get_save_path(id)
cutout_res = cutout_face(save_path,name,save_path)
if cutout_res["status"] == "error":
return put_response(cutout_res)
else:
res["detail"]["faceTotal"] = cutout_res["detail"]["number"]
circum_res = circumscribe_face(save_path,name,save_path)
if circum_res["status"] == "error":
return put_response(circum_res)
return put_response(res)
def upload_file():
files = request.files
res = fm.upload_file(files)
if res["status"] == "success":
name = res["detail"]["name"]
id = res["detail"]["id"]
save_path = fm.get_save_path(id)
cutout_res = cutout_face(save_path, name, save_path)
if cutout_res["status"] == "error":
return put_response(cutout_res)
else:
res["detail"]["faceTotal"] = cutout_res["detail"]["number"]
circum_res = circumscribe_face(save_path, name, save_path)
if circum_res["status"] == "error":
return put_response(circum_res)
print(res)
return put_response(res)
def get_face_image_name(image_id, type="face", number=0, full_path=True):
u"""
return: fullpath name
"""
prefix = type + "_" + (str(number) + "_" if type == "face" else "")
path = get_save_path(image_id)
if path:
image_list = os.listdir(path)
for img in image_list:
if prefix in img:
name = img
break
else:
return None
if full_path:
return os.path.join(path, name)
else:
return name
else:
return None
def get_prob(self, image_id):
save_path = get_save_path(image_id)
face_list = [img for img in os.listdir(save_path) if "face_" in img]
p = {}
for image_name in face_list:
_image_num = re.search(r"_\d+_", image_name).group()
image_num = _image_num[1:][:-1]
CVimage = cv2.imread(save_path + "/" + image_name)
image = self.c.shape_CVimage(CVimage)
with tf.Session() as sess:
ckpt = tf.train.get_checkpoint_state('./')
if ckpt: # checkpointがある場合
last_model = ckpt.model_checkpoint_path # 最後に保存したmodelへのパス
self.saver.restore(sess, last_model) # 変数データの読み込み
#self.saver.restore(sess, "/root/share/domain/model.ckpt")
prob = sess.run(self.softmax,
feed_dict={
self.images_placeholder: [image],
self.keep_prob: 1.0
})[0][0]
if prob:
p[image_num] = float(prob)
else:
res = {
"status": "error",
"message": "can not get valid probability",
}
return res
res = {
"status": "success",
"data_type": "detail",
"detail": {
"probability": p
}
}
return res