大约 3 天前我是 python 的新手，我需要为 iOS 工作项目构建一个原型 python 服务器。我遵循了初始构建的教程。
当我执行“POST”请求时，出现错误。这是我的完整代码，然后是提交“POST”请求时我在终端中收到的错误。
PS。堆栈溢出也是相当新的，所以如果我问错了这个问题，我很抱歉
import flask
from flask import Flask, request, jsonify
from flask_uploads import UploadSet, IMAGES, configure_uploads
from flask import make_response
from flask_sqlalchemy import SQLAlchemy
from flask_marshmallow import Marshmallow
import turicreate as tc
import sys
from queue import Queue
import os
import uuid
import logging
from flask import send_from_directory
import threading
from marshmallow import fields
from marshmallow import post_load
app = Flask(__name__)
if __name__ == "__main__":
# Only for debugging while developing
app.run(host='0.0.0.0', debug=True)
#configure logging
logging.basicConfig( level=logging.DEBUG,
format='[%(levelname)s] - %(threadName)-10s : %(message)s')
#configure images destination folder
app.config['UPLOADED_IMAGES_DEST'] = './images'
images = UploadSet('images', IMAGES)
configure_uploads(app, images)
#configure sqlite database
basedir = os.path.abspath(os.path.dirname(__file__))
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///' + os.path.join(basedir, 'facerecognition.sqlite')
db = SQLAlchemy(app)
ma = Marshmallow(app)
#model/users is a many to many relationship, that means there's a third #table containing user id and model id
users_models = db.Table('users_models',
db.Column("user_id", db.Integer, db.ForeignKey('user.id')),
db.Column("model_id", db.Integer, db.ForeignKey('model.version'))
)
# model table
class Model(db.Model):
version = db.Column(db.Integer, primary_key=True)
url = db.Column(db.String(100))
users = db.relationship('User', secondary=users_models)
# user table
class User(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(300))
position = db.Column(db.String(300))
def __init__(self, name, position):
self.name = name
self.position = position
#user schema
class UserSchema(ma.Schema):
class Meta:
fields = ('id', 'name', 'position')
#model schema
class ModelSchema(ma.Schema):
version = fields.Int()
url = fields.Method("add_host_to_url")
users = ma.Nested(UserSchema, many=True)
# this is necessary because we need to append the current host to the model url
def add_host_to_url(self, obj):
return request.host_url + obj.url
#initialize everything
user_schema = UserSchema()
users_schema = UserSchema(many=True)
model_schema = ModelSchema()
models_schema = ModelSchema(many=True)
db.create_all()
#error handlers
@app.errorhandler(404)
def not_found(error):
return make_response(jsonify({'error': 'not found'}), 404)
@app.errorhandler(400)
def not_found(error):
return make_response(jsonify({'error': 'bad request'}), 400)
#register user
@app.route("/testImages/face-recognition/api/v1.0/user/register", methods=['POST'])
def register_user():
if not request.form or not 'name' in request.form:
return make_response(jsonify({'status': 'failed', 'error': 'bad request', 'message:' : 'Name is required'}), 400)
else:
name = request.form['name']
position = request.form.get('position')
if position is None:
position = ""
newuser = User(name, position)
db.session.add(newuser)
db.session.commit()
if 'photos' in request.files:
uploaded_images = request.files.getlist('photos')
save_images_to_folder(uploaded_images, newuser)
return jsonify({'status' : 'success', 'user' : user_schema.dump(newuser).data })
#function to save images to image directory
def save_images_to_folder(images_to_save, user):
for a_file in images_to_save:
# save images to images folder using user id as a subfolder name
images.save(a_file, str(user.id), str(uuid.uuid4()) + '.')
# get the last trained model
model = Model.query.order_by(Model.version.desc()).first()
if model is not None:
# increment the version
queue.put(model.version + 1)
else:
# create first version
queue.put(1)
@app.route("/testImages/face-recognition/api/v1.0/model/info" , methods=['GET'])
def get_model_info():
models_schema.context['request'] = request
model = Model.query.order_by(Model.version.desc()).first()
if model is None:
return make_response(jsonify({'status': 'failed', 'error': 'model is not ready'}), 400)
else:
return jsonify({'status' : 'success', 'model' : model_schema.dump(model).data})
#serve models
@app.route('/models/')
def download(filename):
return send_from_directory('models', filename, as_attachment=True)
def train_model():
while True:
#get the next version
version = queue.get()
logging.debug('loading images')
data = tc.image_analysis.load_images('images', with_path=True)
# From the path-name, create a label column
data['label'] = data['path'].apply(lambda path: path.split('/')[-2])
# use the model version to construct a filename
filename = 'Faces_v' + str(version)
mlmodel_filename = filename + '.mlmodel'
models_folder = 'models/'
# Save the data for future use
data.save(models_folder + filename + '.sframe')
result_data = tc.SFrame( models_folder + filename +'.sframe')
train_data = result_data.random_split(0.8)
#the next line starts the training process
model = tc.image_classifier.create(train_data, target='label', model='resnet-50', verbose=True)
db.session.commit()
logging.debug('saving model')
model.save( models_folder + filename + '.model')
logging.debug('saving coremlmodel')
model.export_coreml(models_folder + mlmodel_filename)
# save model data in database
modelData = Model()
modelData.url = models_folder + mlmodel_filename
classes = model.classes
for userId in classes:
user = User.query.get(userId)
if user is not None:
modelData.users.append(user)
db.session.add(modelData)
db.session.commit()
logging.debug('done creating model')
# mark this task as done
queue.task_done()
#configure queue for training models
queue = Queue(maxsize=0)
thread = threading.Thread(target=train_model, name='TrainingDaemon')
thread.setDaemon(False)
thread.start()```
这是我在终端中遇到的错误
[DEBUG] - TrainingDaemon : loading images
127.0.0.1 - - [03/Jan/2020 11:52:39] "POST /testImages/face-recognition/api/v1.0/user/register HTTP/1.1" 500 -
[INFO] - Thread-3 : 127.0.0.1 - - [03/Jan/2020 11:52:39] "POST /testImages/face-recognition/api/v1.0/user/register HTTP/1.1" 500 -
Traceback (most recent call last):
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 2463, in __call__
return self.wsgi_app(environ, start_response)
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 2449, in wsgi_app
response = self.handle_exception(e)
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 1866, in handle_exception
reraise(exc_type, exc_value, tb)
File "/Users/me/venv/lib/python3.7/site-packages/flask/_compat.py", line 39, in reraise
raise value
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 2446, in wsgi_app
response = self.full_dispatch_request()
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 1951, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 1820, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "/Users/me/venv/lib/python3.7/site-packages/flask/_compat.py", line 39, in reraise
raise value
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 1949, in full_dispatch_request
rv = self.dispatch_request()
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 1935, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "/Users/me/Desktop/GorillaFace/app.py", line 103, in register_user
save_images_to_folder(uploaded_images, newuser)
File "/Users/me/Desktop/GorillaFace/app.py", line 121, in save_images_to_folder
@app.route("/testImages/face-recognition/api/v1.0/model/info" , methods=['GET'])
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 1314, in decorator
self.add_url_rule(rule, endpoint, f, **options)
File "/Users/me/venv/lib/python3.7/site-packages/flask/app.py", line 90, in wrapper_func
"A setup function was called after the "
AssertionError: A setup function was called after the first request was handled. This usually indicates a bug in the application where a module was not imported and decorators or other functionality was called too late.
To fix this make sure to import all your view modules, database models and everything related at a central place before the application starts serving requests.
Exception in thread TrainingDaemon:
Traceback (most recent call last):
File "/Applications/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.7/lib/python3.7/threading.py", line 917, in _bootstrap_inner
self.run()
File "/Applications/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.7/lib/python3.7/threading.py", line 865, in run
self._target(*self._args, **self._kwargs)
File "/Users/me/Desktop/GorillaFace/app.py", line 159, in train_model
model = tc.image_classifier.create(train_data, target='label', model='resnet-50', verbose=True)
File "/Users/me/venv/lib/python3.7/site-packages/turicreate/toolkits/image_classifier/image_classifier.py", line 225, in create
raise TypeError('"dataset" must be of type SFrame.')
TypeError: "dataset" must be of type SFrame.
我试过的：
就像我说的我还是 python 新手，所以我对 python 代码故障排除知之甚少。断言错误似乎是说没有正确导入某些东西，所以我重新安装了flask-uploads，Flask-SQLAlchemy，flask-marshmallow，marshmallow-sqlalchemy。我还确保所有导入看起来都像教程中那样。
任何人都知道我需要做什么才能不出现此错误？这段代码应该做的是让我将姓名、位置和照片发布到服务器，然后服务器将训练 ML 模型来识别新照片。