def upload_file(): if request.method == 'POST': # Remove existing images in directory files_in_dir = os.listdir(app.config['UPLOAD_FOLDER']) filtered_files = [ file for file in files_in_dir if file.endswith(".jpg") or file.endswith(".jpeg") ] for file in filtered_files: path = os.path.join(app.config['UPLOAD_FOLDER'], file) os.remove(path) # Upload new file if 'file' not in request.files: return redirect(request.url) file = request.files['file'] if not file: return print("GETTING PREDICTION") filename = secure_filename(file.filename) file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename)) prediction, density = get_prediction(file) return render_template('result.html', Prediction=prediction, File=filename, Density=density) return render_template('index.html')
def infer(): # Parse Request req_data = request.get_json() logger.debug(f'req_data: {req_data}') model_id = request.args.get('model_id') if model_id is None: model_id = default_model_id model_inputs_param = request.args.get('model_inputs') if model_inputs_param is None: logger.error(f'No model_inputs found, returning 400') return f'No model_inputs found. {usage_guide}', 400 try: model_inputs = json.loads(model_inputs_param) except json.decoder.JSONDecodeError as e: logger.error( f'Non JSON model_inputs: {model_inputs_param}, returning 400. \n{str(e)}' ) return f'Non JSON model_inputs: {model_inputs_param}. {usage_guide}', 400 logger.debug(f'model_inputs: {model_inputs}') # Predict try: prediction = get_prediction(model_id, model_inputs) except PredictionError as e: logger.error( f'model_inputs: {model_inputs_param}, returning 400. \n{str(e)}') return str(e), 400 return Response(json.dumps(prediction.tolist()), mimetype='application/json')
def predict_url(): url_link = request.args['url_link'] url_image = requests.get(url_link) image_bytes = url_image.content class_id, class_name = get_prediction(image_bytes=image_bytes) class_name = format_class_name(class_name) return render_template('result.html', class_name=class_name)
def upload_file(): if request.method == 'POST': data = [] for key in ['source', 'target']: if key not in request.files: print(f"no {key}") return redirect(request.url) file_obj = request.files.get(key) if not file_obj: print("incorrect file_obj") return print(f"FILE {key}: {file_obj}") wav, sr = read_audio(file_obj) wav = transform_audio(wav, sr) data.append(wav) print("Converting...") result = get_prediction(data[0], data[1]) output = audio_to_bytes(result) return render_template( 'result.html', snd=output, src=audio_to_bytes(data[0].numpy()), tgt=audio_to_bytes(data[1].numpy()) ) return render_template('index.html')
def predictResNet50(): if request.method == 'POST': file_path = get_file_path_and_save(request) im = Image.open(file_path) pred_class, class_name = get_prediction(image_bytes=im) result = format_class_name(class_name) return result return None
def index(): if request.method == 'POST': uploaded_file = request.files['file'] if uploaded_file.filename != '': image_path = os.path.join('static', uploaded_file.filename) uploaded_file.save(image_path) class_name = inference.get_prediction(image_path) print('CLASS NAME', class_name) return render_template('index.html')
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() prediction = get_prediction(image_bytes=img_bytes) return render_template('result.html', class_name=prediction) return render_template('index.html')
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() image = b64encode(img_bytes).decode("utf-8") predict_post = get_prediction(image_bytes=img_bytes) return render_template('result.html', predict_post=predict_post, image=image) return render_template('index.html')
def image_classifier(): print("files", request.files) # if 'file' not in request.files: # return jsonify( message='file not found' ) file = request.files['file'] filename = secure_filename(file.filename) print(filename) file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename)) prediction = get_prediction(UPLOAD_FOLDER + filename) return jsonify(ammount=prediction, )
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() file_tensor = transform_image(image_bytes=img_bytes) ####### class_name = get_prediction(file_tensor) return render_template('result.html', class_name=class_name) return render_template('index.html')
def upload_file(): global model if request.method == "POST": if "file" not in request.files: return redirect(request.url) file = request.files.get("file") if not file: return img_bytes = file.read() class_id = get_prediction(model, image_bytes=img_bytes) return render_template("result.html", class_id=class_id) return render_template("index.html")
def upload_file(): error = "" if request.method == 'POST': img_urls = [request.form['url']] else: img_urls = [ "https://upload.wikimedia.org/wikipedia/en/b/b0/Les-miserables-movie-poster1.jpg" ] try: result = get_prediction(urls=img_urls) except: img_urls = [ "https://upload.wikimedia.org/wikipedia/en/b/b0/Les-miserables-movie-poster1.jpg" ] result = get_prediction(urls=img_urls) error = "Invalid URL format" return render_template('result.html', img_url=img_urls[0], class_name=result, error=error)
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() file_tensor = transform_image(image_bytes=img_bytes) ######## #file_share_ptr = secret_share(file_tensor,workers,hospital) # patient generates secret shares of the data and sends one share to the global agent. class_name = get_prediction(file_tensor) return render_template('result.html', class_name=class_name) return render_template('index.html')
def upload_file(): if request.method == 'GET': return render_template('index.html') if request.method == 'POST': print(request.files) if 'file' not in request.files: print('File not Uploaded..!') return file = request.files['file'] img = file.read() pet_class, pet_name = get_prediction(image_bytes=img) return render_template('results.html', class_id=pet_class, pet=pet_name)
def index(): if request.method == "POST": uploaded_file = request.files["file"] if uploaded_file.filename != "": image_path = os.path.join("static", uploaded_file.filename) uploaded_file.save(image_path) class_name = get_prediction(image_path) result = { "class_name": class_name, "image_path": image_path } return render_template("show.html", result = result) return render_template("index.html")
def predict_image(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() class_id, class_name = get_prediction(image_bytes=img_bytes) class_name = format_class_name(class_name) return render_template('result.html', class_id=class_id, class_name=class_name) return render_template('index.html')
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() mask = get_prediction(image_bytes=img_bytes) mask_to_img = generate_png(img_bytes, mask) return render_template('result.html', mask=mask, img=mask_to_img) return render_template('index.html')
def index(): if request.method =='POST': uploaded_file = request.files['file'] if uploaded_file.filename.endswith('.jpg') or uploaded_file.filename.endswith('.png') or uploaded_file.filename.endswith('.jpeg'): image_path = os.path.join('static', uploaded_file.filename) uploaded_file.save(image_path) class_name = inference.get_prediction(image_path) result = { 'class_name':class_name, 'image_path': image_path } return render_template('show.html', result=result) return render_template('index.html') # by default it will look in templates folder
def upload_file(): if request.method == 'POST': absolute_path = os.path.abspath("../") if 'file' not in request.files: return redirect(request.url) file = request.files['file'] if not file: return print("GETTING PREDICTION") filename = secure_filename(file.filename) file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename)) prediction = get_prediction(file) # Change this to 'file' PATH - ensure format return render_template('result.html', Prediction=prediction, File=filename) # Pass in the prediction return render_template('index.html')
def index(): if request.method == 'POST': #image file is uploaded uploaded_file = request.files['file'] if uploaded_file.filename != '': image_path = os.path.join('static', uploaded_file.filename) uploaded_file.save(image_path) class_name = inference.get_prediction(image_path) print('Class name = ', class_name) result = { 'class_name' : class_name, 'image_path' : image_path, } return render_template('show.html', result = result) return render_template('index.html')
def index(): if request.method == 'POST': uploaded_file = request.files['file'] if uploaded_file.filename != '': image_path = os.path.join('static', uploaded_file.filename) uploaded_file.save(image_path) class_name, n = inference.get_prediction(image_path) #print("Class Name : "+ class_name) result = { 'class_name': class_name, 'image_path': image_path, 'n': n, } return render_template('show.html', result=result) return render_template('index.html') #to the html
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) file = request.files.get('file') if not file: return img_bytes = file.read() class_name = get_prediction(image_bytes=img_bytes) if isinstance(class_name, str) : class_name = format_class_name(class_name[0]) else : class_name = 'No hard hat' return render_template('result.html', class_name=class_name) return render_template('index.html')
def upload_file(): if request.method == 'POST': # if not request.files.get('content', None) or not request.files.get('style', None): # return redirect(request.url) content = request.files.get('content') style = request.files.get('style') full_filename = os.path.join(app.config['UPLOAD_FOLDER'], "target.png") target = get_prediction(content, style) target.save(full_filename) while not os.path.isfile(full_filename): time.sleep(1) return render_template("result.html", image=full_filename) return render_template('index.html')
def upload_file(): if request.method == 'POST': if 'file' not in request.files: return redirect(request.url) # templateから送られてきたFileStorageオブジェクト file = request.files.get('file') if not file: return # クライアントから送られた画像ファイルを読み込める image_bytes = file.read() class_id, class_name = get_prediction(image_bytes) class_name = format_class_name(class_name) return render_template('result.html', class_id=class_id, class_name=class_name) return render_template('index.html')
def upload_file(): if request.method == 'POST': text = request.form.get('textbox') print('text is :', text) # if 'file' not in request.files: # return redirect(request.url) # file = request.files.get('file') # if not file: # return #img_bytes = file.read() img_bytes = text # class_id, class_name = get_prediction(image_bytes=img_bytes) reply = get_prediction(image_bytes=img_bytes) class_name = format_class_name(reply) return render_template('result.html', class_name=class_name) # class_name=class_name) return render_template('index.html')
def index(): if request.method == 'POST': upload_file = request.files['file'] if upload_file.filename != '': image_path = os.path.join('static', upload_file.filename) upload_file.save(image_path) predict_result = inference.get_prediction(image_path) predict_score = predict_result[0] class_name = predict_result[1] result = { 'predict_score': predict_score, 'class_name': class_name, 'image_path': image_path, } return render_template('show.html', result=result) return render_template('index.html')
def index(): # For a POST request, execute this code to infer a result. if request.method == 'POST': # Get the file uploaded in the form. uploaded_file = request.files['file'] # If there is an uploaded file execute this code. if uploaded_file.filename != '': # Define a path for saving this image in the "static" folder. image_path = os.path.join('static', uploaded_file.filename) # Save the uploaded image to display it later. uploaded_file.save(image_path) # Get a class name by making a prediction on the image. class_name = inference.get_prediction(image_path) # Print the class name in the terminal. print('CLASS NAME = ', class_name) # Define an object/dictionary to store the class name and path to the saved image. result = {'class_name': class_name, 'image_path': image_path} # Pass the result to show.html and render the page. return render_template('show.html', result=result) # For a GET request, render index.html return render_template('index.html')
def index(): # when the image has been uploaded if request.method == 'POST': uploaded_file = request.files['file'] if uploaded_file.filename != '': # check if the click was valid ''' ADD A filetype validation here ''' # Saving a copy of the uploaded image to static to display along with the picture image_path = os.path.join( 'static', uploaded_file.filename ) # A unique filaneme creattion method can be used here uploaded_file.save(image_path) # Get the predicted class name from the inference module function class_name = inference.get_prediction(image_path) print('The identified animal is a: {}'.format( class_name)) # Display the result # Result to be displayed result = {'class_name': class_name, 'image_path': image_path} return render_template('show.html', result=result) return render_template('index.html')
def upload_file(): if request.method == 'POST': if 'files[]' not in request.files: return redirect(request.url) files = request.files.getlist('files[]') for file in files: file.save(os.path.join(app.config['UPLOAD_FOLDER'], file.filename)) if not files: return filenames=[] for file in glob.glob(UPLOAD_FOLDER+'/*'): filenames.append(file) results=[] for file in glob.glob(UPLOAD_FOLDER+'/*'): class_name = get_prediction(file) results.append(class_name) #print(filenames) #print(results) for file in glob.glob(UPLOAD_FOLDER+'/*'): os.remove(file) return render_template('result.html', results=results,files=filenames) return render_template('index.html')
def submit_file(): if request.method == 'POST': if 'file' not in request.files: flash('No file part') return redirect(request_url) file = request.files['file'] if file.filename == '': flash('No file selected for uploading') return redirect(request.url) if file: print(file.filename) filename = secure_filename(file.filename) file.save(os.path.join(app.config['UPLOAD_FOLDER'],filename)) new_file = os.path.join(r'C:\Users\NDH60042\MAJOR PROJECT\Flask project',filename) result, accuracy = get_prediction(new_file) if len(result.split())==2: search = "https://www.google.com/search?q=DIY+Reusing+Ideas+for"+result.split()[0]+result.split()[1] else: search = "https://www.google.com/search?q=DIY+Reusing+Ideas+for"+result flash(result) flash(accuracy) flash(filename) webbrowser.open(search) return redirect('/')