app.py

import os
from flask import Flask, render_template, request
import DGS
import random
import StringIO
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
app = Flask(__name__)

UPLOAD_FOLDER = os.path.basename('static')
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

@app.route('/')
def hello_world():
    return render_template('index.html')

@app.route('/upload', methods=['POST'])
def upload_file():
    
    file = request.files['image']
    f = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)

    # add your custom code to check that the uploaded file is a valid image and not a malicious file (out-of-scope for this post)
    file.save(f)
    image='./static/'+file.filename
    print image
    resolution =request.form['resolution']
    density = request.form['density']
    dofilter=request.form['dofilter']
    maxscale=request.form['maxscale']
    mag=int(request.form['mag_he'])
    print request.form['mag_he']
    notes=request.form['notes']
    ans =  DGS.dgs(image, density, resolution, dofilter, maxscale, notes,1)
    print ans
    means=ans['mean grain size']*mag
    kuto = ans['grain size kurtosis']
    stdev = ans['grain size skewness']*mag

    
    y=ans['grain size frequencies']
    x=ans['grain size bins']*mag
    for num in range(len(y)):
        y[num] *= 100
    for num in range(len(x)):
        x[num] *= mag
    print x

    
    
    fig = plt.figure()
    ax = fig.add_subplot(111)
    ax.bar(x,y,align='center',width=means)
    ax.set_xlabel('Grain Size (mm)')
    ax.set_ylabel('Grain Size Frequency' )
    fig.savefig('./static/test.png')
    bar_chart= './static/test.png'
    
    return render_template('output.html',means=means,image=image,stdev=stdev,kuto=kuto,bar_chart=bar_chart)
    
app.run(host='0.0.0.0',debug=False)