def lambda_handler()

in source/super-resolution/src/super_resolution_app.py [0:0]

• 45 lines of code
• 5 McCabe index (conditional complexity)

def lambda_handler(event, context):
    if 'body' not in event:
        return {
            'statusCode': 200,
            'headers': {
                'Access-Control-Allow-Headers': '*',
                'Access-Control-Allow-Origin': '*',
                'Access-Control-Allow-Methods': '*'
            }
        }
    if isinstance(event['body'], str):
        body = json.loads(event['body'])
    else:
        body = event['body']
    if 'url' in body:
        uri = body['url']
        base64_image = Base64Image.from_uri(uri)
    else:
        base64_image = Base64Image.from_base64_image_string(body['img'])
    scale = int(body.get('scale', 2))
    if scale == 4:
        ort_session = ort_session_x4
    else:
        ort_session = ort_session_x2
    pil_image = base64_image.get_pil_image()
    src = np.asarray(pil_image)[:, :, :3]
    in_frame = (np.ascontiguousarray(np.transpose(src, (2, 0, 1))) / 255).astype('float32')
    ort_inputs = {ort_session.get_inputs()[0].name: np.expand_dims(in_frame, 0)}
    ort_outs = ort_session.run(None, ort_inputs)
    rlt = tensor2img(ort_outs[0][0])
    imo = Image.fromarray(rlt)
    buffered = BytesIO()
    imo.save(buffered, format="png")
    img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')

    result = {'result': img_str}
    return {
        'statusCode': 200,
        'headers': {
            'Content-Type': 'application/json',
            'Access-Control-Allow-Headers': 'Content-Type',
            'Access-Control-Allow-Origin': '*',
            'Access-Control-Allow-Methods': 'POST,GET'
        },

        'body': json.dumps(result)
    }