当前，我的Flask应用程序可以在本地计算机上运行，并且可以将主页加载到heroku中。但是，当我调用路由/ predict时，它返回一个（NameError：未定义名称'diagnosis'。）
在/ predict路由中，我尝试两次返回诊断，而不是我通常会尝试的方法。
我确实知道h12是超时错误，但我认为发生这种情况是因为该路由在30秒的时间限制内从未响应。
应用链接 https://lesionlegion1.herokuapp.com/
@app.route('/predict', methods=['GET', 'POST'])
def upload():
# data = {"success": False}
if request.method == 'POST':
print(request)
if request.files.get('file'):
# read the file
file = request.files['file']
# read the filename
# filename = file.filename
# create a path to the uploads folder
# filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
basepath = os.path.dirname(__file__)
filepath = os.path.join(
basepath, 'uploads', secure_filename(file.filename))
# Save the file to the uploads folder
file.save(filepath)
# Load the saved image using Keras and resize it to the Xception
# format of 299x299 pixels
image_size = (75, 100)
im = keras.preprocessing.image.load_img(filepath,
target_size=image_size,
grayscale=False)
# preprocess the image and prepare it for classification
image = prepare_image(im)
global graph
with graph.as_default():
labels = ['Melanocytic nevi', 'Melanoma', 'Benign keratosis-like lesions', 'Basal cell carcinoma',
'Actinic keratoses', 'Vascular lesions', 'Dermatofibroma']
labels = tuple(labels)
global preds
preds = model.predict(image)
# convert preds array to list
preds = preds.tolist()
# convert list of lists to one list for rounding to work
flat_preds = [item for sublist in preds for item in sublist]
updated_preds = list(
map(lambda x: (round(x*100, 3)), flat_preds))
dictionary = dict(zip(labels, updated_preds))
# create a function which returns the value of a dictionary
def keyfunction(k):
return dictionary[k]
global diagnosis
diagnosis = []
# sort by dictionary by the values and print top 3 {key, value} pairs
for key in sorted(dictionary, key=keyfunction, reverse=True)[:3]:
if dictionary[key] > 0:
diagnosis.append([key, str(dictionary[key]) + "%"])
return jsonify(diagnosis)
return jsonify(diagnosis)
if __name__ == "__main__":
app.run(port=5002, debug=True, threaded=False)
heroku日志
2019-03-27T16:47:43.394981+00:00 heroku[router]: at=info method=GET path="/predi
ct" host=lesionlegion1.herokuapp.com request_id=6a8b52fa-33c4-4c23-881f-25a626bc
73ae fwd="96.35.158.2" dyno=web.1 connect=1ms service=5ms status=500 bytes=455 p
rotocol=https
2019-03-27T16:47:43.392702+00:00 app[web.1]: [2019-03-27 16:47:43,390] ERROR in
app: Exception on /predict [GET]
2019-03-27T16:47:43.392716+00:00 app[web.1]: Traceback (most recent call last):
2019-03-27T16:47:43.392719+00:00 app[web.1]: File "/app/.heroku/python/lib/pytho
n3.6/site-packages/flask/app.py", line 2292, in wsgi_app
2019-03-27T16:47:43.392721+00:00 app[web.1]: response = self.full_dispatch_reque
st()
2019-03-27T16:47:43.392723+00:00 app[web.1]: File "/app/.heroku/python/lib/pytho
n3.6/site-packages/flask/app.py", line 1815, in full_dispatch_request
2019-03-27T16:47:43.392725+00:00 app[web.1]: rv = self.handle_user_exception(e)
2019-03-27T16:47:43.392726+00:00 app[web.1]: File "/app/.heroku/python/lib/pytho
n3.6/site-packages/flask/app.py", line 1718, in handle_user_exception
2019-03-27T16:47:43.392728+00:00 app[web.1]: reraise(exc_type, exc_value, tb)
2019-03-27T16:47:43.392729+00:00 app[web.1]: File "/app/.heroku/python/lib/pytho
n3.6/site-packages/flask/_compat.py", line 35, in reraise
2019-03-27T16:47:43.392732+00:00 app[web.1]: raise value
2019-03-27T16:47:43.392734+00:00 app[web.1]: File "/app/.heroku/python/lib/pytho
n3.6/site-packages/flask/app.py", line 1813, in full_dispatch_request
2019-03-27T16:47:43.392735+00:00 app[web.1]: rv = self.dispatch_request()
2019-03-27T16:47:43.392736+00:00 app[web.1]: File "/app/.heroku/python/lib/pytho
n3.6/site-packages/flask/app.py", line 1799, in dispatch_request
2019-03-27T16:47:43.392738+00:00 app[web.1]: return self.view_functions[rule.end
point](**req.view_args)
2019-03-27T16:47:43.392739+00:00 app[web.1]: File "/app/app.py", line 133, in up
load
2019-03-27T16:47:43.392741+00:00 app[web.1]: return jsonify(diagnosis)
2019-03-27T16:47:43.392746+00:00 app[web.1]: NameError: name 'diagnosis' is not
defined
2019-03-27T16:47:43.393556+00:00 app[web.1]: 10.69.185.233 - - [27/Mar/2019:16:4
7:43 +0000] "GET /predict HTTP/1.1" 500 290 "https://lesionlegion1.herokuapp.com
/" "Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gec
ko) Chrome/73.0.3683.86 Safari/537.36"
2019-03-27T16:47:43.396781+00:00 app[web.1]: <Request 'https://lesionlegion1.her
okuapp.com/predict' [POST]>
2019-03-27T16:48:13.443130+00:00 heroku[router]: at=error code=H12 desc="Request
timeout" method=POST path="/predict" host=lesionlegion1.herokuapp.com request_i
d=4ad7f81f-27a9-4b46-9423-24ccb3b59d25 fwd="96.35.158.2" dyno=web.1 connect=0ms
service=30052ms status=503 bytes=0 protocol=https
2019-03-27T16:48:14.067005+00:00 app[web.1]: [2019-03-27 16:48:14 +0000] [4] [CR
ITICAL] WORKER TIMEOUT (pid:101)
2019-03-27T16:48:15.091482+00:00 app[web.1]: [2019-03-27 16:48:15 +0000] [109] [
INFO] Booting worker with pid: 109
答案 0 :(得分：0)
这是因为您的/predict路线同时支持GET和POST请求，但是当您从/predict请求中触及GET路线时，您将返回诊断变量的值：return jsonify(diagnosis)，但未在此范围内定义此diagnosis变量，而是在您的POST中将其定义为全局变量路线，所以这就是为什么出现以下错误：
NameError：名称“诊断”未定义
您可以在堆栈跟踪的这一部分中看到这是由您的GET方法引起的：
2019-03-27T16：47：43.394981 + 00：00 heroku [router]：at = info method = GET path =“ / predi ct“ host = lesionlegion1.herokuapp.com request_id = 6a8b52fa-33c4-4c23-881f-25a626bc 73ae fwd =“ 96.35.158.2” dyno = web.1 connect = 1ms服务= 5ms状态= 500字节= 455 p rotocol = https 2019-03-27T16：47：43.392702 + 00：00 app [web.1]：[2019-03-27 16：47：43,390]错误 应用：/ predict [GET]
异常
因此，要解决此错误，您需要在处理特定请求类型之前声明diagnosis变量，类似以下内容：
@app.route('/predict', methods=['GET', 'POST'])
def upload():
diagnosis = []
if request.method == 'POST':
# ... handle POST request
return jsonify(diagnosis)
# Default response for GET requests
return jsonify(diagnosis)
if __name__ == "__main__":
app.run(port=5002, debug=True, threaded=False)
希望有帮助！