flask_crop_predict_fn.py

@app.route('/predict', methods=['GET', 'POST'])
def upload():
    # Get the file from post request
    if request.method == 'POST':
        # Save the file to ./uploads
        f = request.files['image']
        
        # path to save image file
        basepath = os.path.dirname(__file__)
        img_path = os.path.join(
            basepath, 'uploads', secure_filename(f.filename))
        f.save(img_path)# save image to uploads folder.
        
        # one class clasification model
        leaf = leaf_predict(img_path)
        # condition if leaf was pass for predict
        if leaf == "leaf":
            # Make prediction
            preds = model_predict(img_path)
            rows = info()
            res = np.asarray(rows[preds])
            value = (preds == int(res[0]))
            if value:
                ID, Disease, Pathogen, Symptoms, Management = [i for i in res]
            return render_template('result.html', Pathogen=Pathogen, Symptoms=Symptoms, Management=Management, result=Disease, filee=f.filename)
        else:
            return render_template('index.html', Error="ERROR: UPLOADED IMAGE IS NOT A LEAF (OR) MORE LEAVES IN ONE IMAGE")
        # return result
    return None