forms.py

from django import forms
from .models import Inference
from keras.preprocessing import image
from keras.models import model_from_json
import numpy as np


class InferenceForm(forms.ModelForm):
    class Meta : 
        model  = Inference
        fields = ('image','prediction')
    def create(self,valldated_data):
        inference_obj = Inference.objects.create(**validated_data)
        
        # HERE WHERE YOU CAN PUT YOUR OWN MODEL PATH
        
        model_json_path   = '../model/model_architecture.json'
        model_weight_path = '../model/model_weights.h5'
        
        # load the image file an turn it to a numpy array 
        img = image.load_img(inference_obj.image.file.filename,target_size=(150,150))
        img_array = image.img_to_array(img)
        img_array.shape = (1,150,150,3)
        
        # load model model_architecture
        self.update_state(state='load model', meta={'progress': 25})
        with open('../model/model_architecture.json', 'r') as f:
            model = model_from_json(f.read())
        # load model weights
        model.load_weights('../model/model_weights.h5')
        
        # make image prediction 
        prediction = model.predict(img_array,verbose=1) 
        if prediction == 0 : 
            result  = 'Normal'
        elif prediction == 1 : 
            result  = 'PNEUMONIA'
            
        inference_obj.prediction = result               
        return inference_obj