def prediction():
image_id = request.json.get('img_id')
question = request.json.get('question')
img = Image.get(image_id)
if img is None:
kwargs = {'status': 'error', 'message': 'invalid image id'}
response = jsonify(kwargs)
response.status_code = 400
else:
filepath = os.path.join(Config.UPLOAD_DIR, img.filename)
path = os.path.join(Config.STATIC_DIR, f'{filepath}')
pred, fig_id = asyncio.run(run_model(path, question))
if fig_id > 0:
#fig = WeightFigure.get(fig_id)
#figfile = fig.filename
#figpath = os.path.join(Config.FIG_DIR, figfile)
pass
kwargs = {'status': 'success'}
data = {'prediction': pred}
response = jsonify(data=data, **kwargs)
response.status_code = 200
return response
def extract_qa_by_request_log(req_id):
log = RequestLog.get(req_id)
kwargs = {
'status': 'success',
'task': 'read-only',
'type': 'request log',
}
data = {
'request_id': req_id,
'question': Question.get(log.question_id).question,
'prediction': log.score.prediction,
'image': Image.get(log.image_id).filename,
'figure': WeightFigure.get(log.fig_id).filename,
}
response = jsonify(data=data, **kwargs)
response.status_code = 200
return response