nwatab/SupportersColabJune1.jpg

## dog.jpg

      
    Raw
  

              dog.jpg
            
          
## flask_sample_1_hello_world.py
from flask import Flask
app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello, World!'

if __name__ == '__main__':
    app.run()

## flask_sample_2_endpoints.py
from flask import Flask
app = Flask(__name__)

@app.route('/')
def index():
    return 'Index Page'

@app.route('/hello')
def hello():
    return 'Hello, World'

@app.route('/users/<username>')
def show_user_profile(username):
    # show the user profile for that user
    return 'User %s' % username

if __name__ == '__main__':
    app.run()

## flask_sample_3_REST_API.py
from flask import Flask, jsonify
app = Flask(__name__)

@app.route('/users')
@app.route('/users/<int:id>')
def users(id=None):
    print(id)
    users = [
              {'id': 1, 'name': 'Alice'},
              {'id': 2, 'name': 'Bob'},
              {'id': 3, 'name': 'Charlie'}]
    if id is None:
        return jsonify(users)
    elif isinstance(id, int) and 1 <= id <= 3:
        return jsonify({'id': id, 'name': users[id-1]['name']})
    else:
        return jsonify({})

if __name__ == '__main__':
    app.run()

## flask_sample_4_image_uploader.py
import os
from flask import Flask, request, redirect, url_for, jsonify
from werkzeug.utils import secure_filename

UPLOAD_FOLDER = 'uploaded'
os.makedirs(UPLOAD_FOLDER, exist_ok=True)
ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg', 'gif'])

app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

def allowed_file(filename):
    return '.' in filename and \
           filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS

@app.route('/', methods=['GET', 'POST'])
def upload_file():
    if request.method == 'POST':
        # check if the post request has the file part
        if 'file' not in request.files:
            return redirect(request.url)
        file = request.files['file']
        # if user does not select file, browser also
        # submit a empty part without filename
        if file.filename == '':
            return redirect(request.url)
        if file and allowed_file(file.filename):
            filename = secure_filename(file.filename)
            file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
            return jsonify(filename=filename,
                           type=filename.rsplit('.', 1)[1].lower())
   return '''
    <!doctype html>
    <title>Upload new File</title>
    <h1>Upload new File</h1>
    <form method=post enctype=multipart/form-data>
      <p><input type=file name=file>
         <input type=submit value=Upload>
    </form>
    '''
if __name__ == '__main__':
    app.run()

## keras_flask_vgg_api.py
import os
from flask import Flask, request, redirect, url_for, jsonify, Response
from werkzeug.utils import secure_filename

from keras.applications.vgg16 import VGG16, preprocess_input, decode_predictions
from keras.preprocessing import image
import numpy as np
from PIL import Image
import io

app = Flask(__name__)
model = None

def load_model():
    global model
    model = VGG16(weights='imagenet', include_top=True)

@app.route('/', methods=['GET', 'POST'])
def upload_file():
    response = {'success': False}
    if request.method == 'POST':
        if request.files.get('file'):
            img_requested = request.files['file'].read()
            img = Image.open(io.BytesIO(img_requested))
            if img.mode != 'RGB':
                img = img.convert('RGB')
            img = img.resize((224, 224))
            img = image.img_to_array(img)
            img = np.expand_dims(img, axis=0)
            inputs = preprocess_input(img)

            preds = model.predict(inputs)
            results = decode_predictions(preds)

            response['predictions'] = []
            for (imagenetID, label, prob) in results[0]:
                row = {'label': label, 'probability': float(prob)}
                response['predictions'].append(row)
            response['success'] = True
            return jsonify(response)

    return '''
    <!doctype html>
    <title>Upload new File</title>
    <h1>Upload new File</h1>
    <form method=post enctype=multipart/form-data>
      <p><input type=file name=file>
         <input type=submit value=Upload>
    </form>
    '''

if __name__ == '__main__':
    load_model()
    # no-thread: https://github.com/keras-team/keras/issues/2397#issuecomment-377914683
    # avoid model.predict runs before model initiated
    app.run(threaded=False)

## keras_vgg_1_summary.py
from keras.applications.vgg16 import VGG16

model = VGG16(weights='imagenet', include_top=True)
print(model.summary())

## keras_vgg_2_image_recognition.py
from keras.applications.vgg16 import VGG16, preprocess_input, decode_predictions
from keras.preprocessing import image
import numpy as np

img_path = 'cat.jpg' # change to your file
model = VGG16(weights='imagenet', include_top=True)
img = image.load_img(img_path, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)

pred = model.predict(x)
label = decode_predictions(pred)
print(label)

## requirements.txt
absl-py==0.2.1
astor==0.6.2
bleach==1.5.0
click==6.7
Flask==1.0.2
gast==0.2.0
grpcio==1.12.0
h5py==2.7.1
html5lib==0.9999999
itsdangerous==0.24
Jinja2==2.10
Keras==2.1.6
Markdown==2.6.11
MarkupSafe==1.0
numpy==1.14.3
Pillow==5.1.0
protobuf==3.5.2.post1
PyYAML==3.12
scipy==1.1.0
six==1.11.0
tensorboard==1.8.0
tensorflow==1.8.0
termcolor==1.1.0
Werkzeug==0.14.1

## SupportersColabJune1.jpg

      
    Raw
  

              SupportersColabJune1.jpg
	from flask import Flask
	app = Flask(__name__)

	@app.route('/')
	def hello_world():
	return 'Hello, World!'

	if __name__ == '__main__':
	app.run()
	from flask import Flask, jsonify
	app = Flask(__name__)

	@app.route('/users')
	@app.route('/users/<int:id>')
	def users(id=None):
	print(id)
	users = [
	{'id': 1, 'name': 'Alice'},
	{'id': 2, 'name': 'Bob'},
	{'id': 3, 'name': 'Charlie'}]
	if id is None:
	return jsonify(users)
	elif isinstance(id, int) and 1 <= id <= 3:
	return jsonify({'id': id, 'name': users[id-1]['name']})
	else:
	return jsonify({})

	if __name__ == '__main__':
	app.run()
	import os
	from flask import Flask, request, redirect, url_for, jsonify
	from werkzeug.utils import secure_filename

	UPLOAD_FOLDER = 'uploaded'
	os.makedirs(UPLOAD_FOLDER, exist_ok=True)
	ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg', 'gif'])

	app = Flask(__name__)
	app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

	def allowed_file(filename):
	return '.' in filename and \
	filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS

	@app.route('/', methods=['GET', 'POST'])
	def upload_file():
	if request.method == 'POST':
	# check if the post request has the file part
	if 'file' not in request.files:
	return redirect(request.url)
	file = request.files['file']
	# if user does not select file, browser also
	# submit a empty part without filename
	if file.filename == '':
	return redirect(request.url)
	if file and allowed_file(file.filename):
	filename = secure_filename(file.filename)
	file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
	return jsonify(filename=filename,
	type=filename.rsplit('.', 1)[1].lower())
	return '''
	<!doctype html>
	<title>Upload new File</title>
	<h1>Upload new File</h1>
	<form method=post enctype=multipart/form-data>
	<p><input type=file name=file>
	<input type=submit value=Upload>
	</form>
	'''
	if __name__ == '__main__':
	app.run()
	from keras.applications.vgg16 import VGG16

	model = VGG16(weights='imagenet', include_top=True)
	print(model.summary())
	from keras.applications.vgg16 import VGG16, preprocess_input, decode_predictions
	from keras.preprocessing import image
	import numpy as np

	img_path = 'cat.jpg' # change to your file
	model = VGG16(weights='imagenet', include_top=True)
	img = image.load_img(img_path, target_size=(224, 224))
	x = image.img_to_array(img)
	x = np.expand_dims(x, axis=0)
	x = preprocess_input(x)

	pred = model.predict(x)
	label = decode_predictions(pred)
	print(label)
	absl-py==0.2.1
	astor==0.6.2
	bleach==1.5.0
	click==6.7
	Flask==1.0.2
	gast==0.2.0
	grpcio==1.12.0
	h5py==2.7.1
	html5lib==0.9999999
	itsdangerous==0.24
	Jinja2==2.10
	Keras==2.1.6
	Markdown==2.6.11
	MarkupSafe==1.0
	numpy==1.14.3
	Pillow==5.1.0
	protobuf==3.5.2.post1
	PyYAML==3.12
	scipy==1.1.0
	six==1.11.0
	tensorboard==1.8.0
	tensorflow==1.8.0
	termcolor==1.1.0
	Werkzeug==0.14.1