def predict_label():
_data = Data()
labels = _data.labels
if request.method == 'GET':
data = _data.test_data
image_data = get_image_data(data)
prediction = predict_image(image_data)
argmax = int(np.argmax(np.array(prediction)[0]))
return jsonify({labels[argmax]: prediction[0][argmax]})
elif request.method == 'POST':
input_data = request.get_json()
raw_data = input_data["image_data"]
decoded = base64.b64decode(str(raw_data))
io_bytes = io.BytesIO(decoded)
data = Image.open(io_bytes)
image_data = get_image_data(data)
prediction = predict_image(image_data)
argmax = int(np.argmax(np.array(prediction)[0]))
job_id = data['job_id'] if 'job_id' in input_data.keys(
) else get_job_id()
return jsonify({
labels[argmax]: prediction[0][argmax],
'job_id': job_id
})
async def post_redirect(redirect_path: str, data: Data,
background_tasks: BackgroundTasks) -> Dict[str, Any]:
data.data['job_id'] = get_job_id()
logger.info(
f'POST redirect abtest to: /{redirect_path} as {data.data["job_id"]} with group {data.ab_test}'
)
if data.ab_test.upper() in ServiceConfigurations.ab_test_group.keys():
group_alias = ServiceConfigurations.ab_test_group[data.ab_test.upper()]
customized_redirect_map = {
group_alias:
ServiceConfigurations.customized_redirect_map[group_alias]
}
else:
customized_redirect_map = ServiceConfigurations.customized_redirect_map
if ServiceConfigurations.enqueue:
store_data_job._save_data_job(data.data, data.data['job_id'],
background_tasks, True)
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(
total=2)) as session:
tasks = [
asyncio.ensure_future(
_post_redirect(
session,
helpers.customized_redirect_builder(
k, v, redirect_path, customized_redirect_map),
data.data, k))
for k, v in ServiceConfigurations.urls.items()
if k in customized_redirect_map.keys()
]
responses = await asyncio.gather(*tasks)
logger.info(f'responses: {responses}')
return responses
def predict():
_data = Data()
if request.method == 'GET':
data = _data.test_data
image_data = get_image_data(data)
prediction = predict_image(image_data)
return jsonify({'prediction': prediction})
elif request.method == 'POST':
input_data = request.get_json()
raw_data = input_data["image_data"]
decoded = base64.b64decode(str(raw_data))
io_bytes = io.BytesIO(decoded)
data = Image.open(io_bytes)
image_data = get_image_data(data)
prediction = predict_image(image_data)
job_id = data['job_id'] if 'job_id' in input_data.keys(
) else get_job_id()
return jsonify({'prediction': prediction, 'job_id': job_id})
def predict():
_data = Data()
if request.method == "GET":
data = _data.test_data
image_data = get_image_data(data)
prediction = predict_image(image_data)
return jsonify({"prediction": prediction})
elif request.method == "POST":
input_data = request.get_json()
raw_data = input_data["image_data"]
decoded = base64.b64decode(str(raw_data))
io_bytes = io.BytesIO(decoded)
data = Image.open(io_bytes)
image_data = get_image_data(data)
prediction = predict_image(image_data)
job_id = data["job_id"] if "job_id" in input_data.keys(
) else get_job_id()
return jsonify({"prediction": prediction, "job_id": job_id})
async def post_redirect(redirect_path: str, data: Data,
background_tasks: BackgroundTasks) -> Dict[str, Any]:
data.data["job_id"] = get_job_id()
logger.info(f'POST redirect to: /{redirect_path} as {data.data["job_id"]}')
if ServiceConfigurations.enqueue:
store_data_job._save_data_job(data.data, data.data["job_id"],
background_tasks, True)
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(
total=2)) as session:
tasks = [
asyncio.ensure_future(
_post_redirect(
session,
helpers.customized_redirect_builder(
k, v, redirect_path,
ServiceConfigurations.customized_redirect_map),
data.data, k))
for k, v in ServiceConfigurations.urls.items()
]
responses = await asyncio.gather(*tasks)
logger.info(f"responses: {responses}")
return responses
async def predict_label(data: Data,
background_tasks: BackgroundTasks = BackgroundTasks()):
job_id = data.job_id if data.job_id is not None else get_job_id()
return await _predict._predict_label(data, job_id, background_tasks)
async def predict(data: Data,
background_tasks: BackgroundTasks = BackgroundTasks()):
job_id = data.job_id if data.job_id is not None else get_job_id()
result = await _predict_image._predict(data, job_id, background_tasks)
return result
async def predict_async(data: Data, background_tasks: BackgroundTasks):
job_id = data.job_id if data.job_id is not None else get_job_id()
return await _predict._predict_async_post(data, job_id, background_tasks)
async def predict(data: Data,
background_tasks: BackgroundTasks = BackgroundTasks()):
job_id = data.job_id if data.job_id is not None else get_job_id()
return await _predict_ab_test._predict(data, job_id, background_tasks,
AB_TEST_GROUP)
