def upload():
try:
image = request.files['image'].read()
eg_processor.process_image(image)
return send_file('/ekholabs/face-classifier/result/predicted_image.png', mimetype='image/png')
except Exception as err:
logging.error('An error has occurred whilst processing the file: "{0}"'.format(err))
abort(400)
def upload():
try:
image = request.files['image'].read()
eg_processor.process_image(image)
return send_file(
str(pathlib.Path(__file__).parent.parent.parent.absolute()) +
'/result/predicted_image.png',
mimetype='image/png')
except Exception as err:
logging.error('No pudimos procesar la imagen enviada ' + str(err))
abort(400)
def upload():
try:
image = request.files.get('image')
if not image:
return make_response('Please provide \'image\' for detect.\n', 400)
filename = str(uuid.uuid4()) + '-' + image.filename
eg_processor.process_image(image.read(), filename,
app.config.get('model_path'))
return make_response(jsonify(convert_data(filename)), 200)
except Exception as err:
logging.error(
'An error has occurred whilst processing the file: "{0}"'.format(
err))
abort(400)
def upload():
try:
image = request.files['image'].read()
emotions = eg_processor.process_image(image)
return jsonify(emotions)
except Exception as err:
logging.error('An error has occurred whilst processing the file: "{0}"'.format(err))
abort(400)
def upload():
try:
image = request.files['image'].read()
emotion = eg_processor.process_image(image)
return jsonify(emotion)
except Exception as err:
logging.error(
'An error has occurred whilst processing the file: "{0}"'.format(
err))
abort(400)
def classifyImage():
# image = request.files['image'].read()
# print(image[:10], "this is image")
dataUrl = request.form["dataUrl"]
print("this is data url", dataUrl[:100])
content = dataUrl.split(';')[1]
img_encoded = content.split(',')[1]
body = base64.decodebytes(img_encoded.encode("utf-8"))
# jsonInfo =
full_filepath = eg_processor.process_image(body)
return render_template(CLASSIFY_IMAGE_TEMPLATE, result_img=full_filepath)
def upload():
try:
image = request.files['image'].read()
emotion_text = eg_processor.process_image(image)
except Exception as e:
logging.error(traceback.format_exc())
return make_response(
jsonify({
'error':
'An error has occurred whilst processing the file: "{0}"'.
format(e)
}), 500)
#logging.error('An error has occurred whilst processing the file: "{0}"'.format(e))
#abort(400)
else:
return make_response(jsonify({'emotion': emotion_text}), 200)
def upload(ret_type):
try:
# with open('/tmp/debug.txt', "w+") as debug_file:
# print("bp A".format(), file=debug_file)
image = request.files['image'].read()
result_path = '/tmp/result.png'
ret_array = eg_processor.process_image(image, result_path)
if ret_type == 'label':
return jsonify(ret_array)
elif ret_type == 'mark':
return send_file(result_path, mimetype='image/png')
else:
return 'unknown ret_type ' + ret_type
except Exception as err:
logging.error(
'An error has occurred whilst processing the file: "{0}"'.format(
err))
abort(400)
def upload():
try:
image = ''
if 'application/json' in request.content_type:
image = base64.b64decode(request.get_json()['image'])
elif 'multipart/form-data' in request.content_type:
image = request.files['image'].read()
else:
image = base64.b64decode(request.get_data())
faces = eg_processor.process_image(image)
response = make_response(jsonify(faces), 200)
response.headers['Content-Type'] = 'application/json'
return response
except Exception as err:
logging.error(
'An error has occurred whilst processing the file: "{0}"'.format(
err))
abort(400)
def upload():
"""
上传图片，并返回识别结果
:return:
"""
res = dict()
res['data'] = 1
filename = photos.save(request.files['photo'])
# 获取原始图片
unchanged_image = cv2.imread(UPLOAD_DIR + "/" + filename)
# 获取情绪，性别信息
face_size, gender, emotion = eg_processor.process_image(
unchanged_image)
results = []
# 面部特征结果
face_detail = list()
face_detail_dict = apply(unchanged_image)
print(face_detail_dict.keys())
for k in face_detail_dict.keys():
face_detail.append(
Node(contents=[
face_detail_dict[k]['type'] + "\n" +
face_detail_dict[k]['detail']
],
dtype="text",
style="padding-top:10px").to_dict())
result = Result(title="面部特征",
detail=Node(contents=face_detail).to_dict()).to_dict()
results.append(result)
# 健康特征结果
health_detail = list()
health_detail.append(
Node(style="padding-top:10px",
dtype="text",
contents=["1. 保健原则：益气固表，健脾和胃"]).to_dict())
health_detail.append(
Node(style="padding-top:10px",
dtype="text",
contents=["2. 起居养生：早睡早起，保证睡眠充足，四季起居有常；适度运动，避免过度体力劳动．"
]).to_dict())
health_detail.append(
Node(style="padding-top:10px",
dtype="text",
contents=[
"3. 饮食药膳：现在是小满，我国古代将小满分为三候：\n“一候苦菜秀;二候靡草死;\
三候麦秋至。”《周书》中，即有“小满之日苦菜秀”之说。小满时节的气候较为潮湿，所以适宜食用一些祛湿类的食物，如番茄，西瓜。"
]).to_dict())
health_detail.append(
Node(dtype="image",
contents=["/images/baidu/fanqie.jpeg"]).to_dict())
health_detail.append(
Node(dtype="text",
contents=[
"这是最好的防晒食物。番茄富含抗氧化剂番茄红素，每天摄入16毫克番茄红素可将晒伤的危险系数下降40%。"
]).to_dict())
health_detail.append(
Node(dtype="image",
contents=["/images/baidu/xigua.jpg"]).to_dict())
health_detail.append(
Node(dtype="text",
contents=["西瓜含水量在水果中是首屈一指的，所以特别适合补充人体水分的损失。"]).to_dict())
health_result = Result(
title="健康状况：气虚，肾虚",
more="详细诊断 >",
detail=Node(contents=health_detail).to_dict()).to_dict()
results.append(health_result)
res['face_size'] = face_size
res['results'] = results
res['image_url'] = photos.url(filename)
story_json = json.dumps(res)
openid = request.args.get("openid")
print(openid)
if openid is not None:
# 保存记录到数据库
print("保存用户记录到数据库" + openid)
print(UserInfo.query.all())
user_info = UserInfo.query.filter_by(openid=openid).first()
print(user_info)
if user_info is not None:
story = FaceStory(openid, user_info.nick_name,
user_info.avatar_url, story_json)
db.session.add(story)
db.session.flush()
db.session.refresh(story)
db.session.commit()
return Response(json.dumps(story.to_dict()),
mimetype='application/json')
return Response(story_json, mimetype='application/json')