def predict_image():
if request.method == 'POST':
# Step 1: check if the post request has the file part
if 'file' not in request.files:
return jsonify('No file found'), 400
file = request.files('file')
# Step 2: Basic file extension validation
if file and allowed_file(file.filename):
# Step 3: Save the file
# Note, in production, this would require careful
# validation, management and clean up
file.save(os.path.join(UPLOAD_FOLDER, filename))
_logger.debug(f'Inputs: {filename}')
# Step 4: perform predictions
result = make_single_prediction(
image_name=filename,
image_directory=UPLOAD_FOLDER)
_logger.debug(f'Outputs: {result}')
readable_predictions = result.get('readable_predictions')
version = result.get('version')
# Step 5: Return the response as JSON
return jsonify({'readable_predictions': readable_predictions[0],
'version': version})
def predict_video():
if request.method == 'POST':
#check if the post request has the file part
if 'file' not in request.files:
return jsonify('no file found') , 400
file=request.files['file']
#Basic file extension validation
if file and allowed_file(file.filename):
filename=secure_filename(file.filename)
# save the file to upload directory
file.save(os.path.join(UPLOAD_FOLDER,filename))
_logger.debug(f'inputs: {filename}')
#perform predction
result =make_single_prediction(video_name=filename,
video_directory=UPLOAD_FOLDER)
_logger.debug(f'Outputs: {result}')
readable_predictions = result.get('readable_predictions')
version = result.get('version')
# return the output results
return jsonify(
{'readable_predictions': readable_predictions[0],
'version': version})
