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Keras - Django Web App
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| <html> | |
| <head> | |
| <title>Arda Mavi - App</title> | |
| </head> | |
| <body> | |
| <center> | |
| <a style="text-decoration: none; font-size: 6em;" href="/"> | |
| <span style="color:#fc4f3f;">Arda Mavi</span> <span style="color:#808080"></span> <span style="color:#3377CC;">App</span> | |
| </a> | |
| <br/><br/><br/> | |
| <form method="post" action="/predict" enctype="multipart/form-data"> | |
| {% csrf_token %} | |
| <input type="file" name="image" accept="image/*" apture="camera"> | |
| <br/><br/> | |
| <button style="width: 100PX;" type="submit"><span>Predict</span></button> | |
| </form> | |
| <h4 style="color: #4a84cc;">{{ result|safe }}</h4> | |
| <br/> | |
| <h5 style="color: #515151;">Source: <a href="https://github.com/ardamavi" target="_blank" style="color: #515151; text-decoration: none;">github.com/ardamavi</a></h5> | |
| <span style="color:#656565;">Copyright © 2017</span> | |
| <br/> | |
| <a style="text-decoration: none; font-size: 1.5em;" href="http://github.com/ardamavi.com" target="_blank"><span style="color:#808080">By</span> <span style="color:#fc4f3f;">Arda</span> <span style="color:#3377CC;">Mavi</span></a> | |
| </center> | |
| </body> | |
| </html> |
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| # Arda Mavi | |
| # Django views.py file: | |
| from django.http import HttpResponse | |
| from django.shortcuts import render | |
| from keras.models import model_from_json | |
| from scipy.misc import imresize | |
| from PIL import Image | |
| import numpy as np | |
| def index(request): | |
| return render(request, 'index.html', {'result': "Results"}) | |
| def predict(request): | |
| sonuc = 'Error!' | |
| if request.method == 'POST' and request.FILES: | |
| file_img = Image.open(request.FILES['image']) | |
| image = np.array(file_img) | |
| image = imresize(image, (200,200, 3)) | |
| image = image.reshape(1, 200, 200, 3) | |
| model_file = open('static/model.json', 'r') | |
| model = model_file.read() | |
| model_file.close() | |
| model = model_from_json(model) | |
| model.load_weights("static/weights.h5") | |
| Y = model.predict(image) | |
| result = np.argmax(Y, axis=1) | |
| result = "<span style='color:#fc4f3f; font-size: 2em;'>{0}</span>".format(result) | |
| else: | |
| sonuc = "<span style='color:#fc4f3f;'>Your file couldn't found!</span>" | |
| return render(request, 'index.html', {'result': result}) | |
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