LucasMagnum/app.py

## app.py
import json

from flask import Flask, request

from fastai.vision import open_image, load_learner

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


learner = load_learner("./")


@app.route('/', methods=['GET', 'POST'])
def upload_file():
    predicts = ""

    if request.method == 'POST' and 'file' in request.files:
        # check if the post request has the file part
        file = request.files['file']

        img = open_image(file)
        _, _, losses = learner.predict(img)

        predicts = json.dumps({
            "filename": file.filename,
            "predictions": sorted(
                zip(learner.data.classes, map(lambda l: "%2.f%%" % (float(l) * 100), losses)),
                key=lambda p: p[1],
                reverse=True
            )
        })

    return '''
    <!doctype html>
    <title>Quem é?</title>
    <h1>Quem é?</h1>
    <form method=post enctype=multipart/form-data>
      <p><input type=file name=file>
         <input type=submit value=Upload>
    </form>
    %s
    ''' % predicts
	import json

	from flask import Flask, request

	from fastai.vision import open_image, load_learner

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


	learner = load_learner("./")


	@app.route('/', methods=['GET', 'POST'])
	def upload_file():
	predicts = ""

	if request.method == 'POST' and 'file' in request.files:
	# check if the post request has the file part
	file = request.files['file']

	img = open_image(file)
	_, _, losses = learner.predict(img)

	predicts = json.dumps({
	"filename": file.filename,
	"predictions": sorted(
	zip(learner.data.classes, map(lambda l: "%2.f%%" % (float(l) * 100), losses)),
	key=lambda p: p[1],
	reverse=True
	)
	})

	return '''
	<!doctype html>
	<title>Quem é?</title>
	<h1>Quem é?</h1>
	<form method=post enctype=multipart/form-data>
	<p><input type=file name=file>
	<input type=submit value=Upload>
	</form>
	%s
	''' % predicts