def update_model():
model_uri = request.args.get('model_uri')
model_dir = request.args.get('model_dir')
if not model_uri and not model_dir:
return ('missing model_uri or model_dir')
print('[INFO] Update Model ...', flush=True)
if model_uri:
print('[INFO] Got Model URI', model_uri, flush=True)
#FIXME webmodule didnt send set detection_mode as Part Detection somtimes.
# workaround
onnx.set_detection_mode('PD')
onnx.set_is_scenario(False)
if model_uri == onnx.model_uri:
print('[INFO] Model Uri unchanged', flush=True)
else:
get_file_zip(model_uri, MODEL_DIR)
onnx.model_uri = model_uri
onnx.update_model('model')
print('[INFO] Update Finished ...', flush=True)
return 'ok'
elif model_dir:
print('[INFO] Got Model DIR', model_dir)
onnx.set_is_scenario(True)
onnx.update_model(model_dir)
print('[INFO] Update Finished ...')
return 'ok'
def update_model():
model_uri = request.args.get('model_uri')
model_dir = request.args.get('model_dir')
if not model_uri and not model_dir:
return ('missing model_uri or model_dir')
print('[INFO] Update Model ...')
if model_uri:
print('[INFO] Got Model URI', model_uri)
if model_uri == onnx.model_uri:
print('[INFO] Model Uri unchanged')
else:
get_file_zip(model_uri, MODEL_DIR)
onnx.model_uri = model_uri
onnx.update_model('model')
print('[INFO] Update Finished ...')
return 'ok'
elif model_dir:
print('[INFO] Got Model DIR', model_dir)
onnx.update_model(model_dir)
print('[INFO] Update Finished ...')
return 'ok'
def update_model():
model_uri = request.args.get("model_uri")
model_dir = request.args.get("model_dir")
if not model_uri and not model_dir:
return "missing model_uri or model_dir"
logger.info("Update Model ...")
if model_uri:
logger.info("Got Model URI %s", model_uri)
if model_uri == onnx.model_uri:
logger.info("Model URI unchanged")
else:
get_file_zip(model_uri, MODEL_DIR)
onnx.model_uri = model_uri
onnx.update_model("model")
logger.info("Update Finished ...")
return "ok"
elif model_dir:
print("[INFO] Got Model DIR", model_dir)
onnx.update_model(model_dir)
print("[INFO] Update Finished ...")
return "ok"
def update_model():
model_uri = request.args.get('model_uri')
if not model_uri: return ('missing model_uri')
print('[INFO] Update Model ...')
if model_uri == onnx.model_uri:
print('[INFO] Model Uri unchanged')
return 'ok'
get_file_zip(model_uri, MODEL_DIR)
onnx.model_uri = model_uri
onnx.update_model('model')
print('[INFO] Update Finished ...')
return 'ok'
def run(self, model_uri, MODEL_DIR):
self.lock.acquire()
try:
print("Downloading URL.", flush=True)
get_file_zip(model_uri, MODEL_DIR)
print("Downloading URL..., Complete!!!", flush=True)
self.lock.release()
self.model_downloading = False
print("Updating Model...", flush=True)
self.update_model("model")
print("Updating Model..., Complete!!!", flush=True)
except Exception:
self.lock.release()
self.model_downloading = False
print("Download URL failed. Model_URI: %s, MODEL_DIR: %s" %
(model_uri, MODEL_DIR))
traceback.print_exc()
def twin_update_listener(client):
while True:
patch = client.receive_twin_desired_properties_patch() # blocking call
print("[INFO] Twin desired properties patch received:", flush=True)
print("[INFO]", patch, flush=True)
if "model_uri" not in patch:
print("[WARNING] missing model_uri", flush=True)
continue
model_uri = patch["model_uri"]
print("[INFO] Got Model URI", model_uri, flush=True)
if model_uri == onnx.model_uri:
print("[INFO] Model Uri unchanged", flush=True)
else:
get_file_zip(model_uri, MODEL_DIR)
onnx.model_uri = model_uri
onnx.update_model("model")
print("[INFO] Update Finished ...", flush=True)
def module_twin_callback(self, update_state, payload, user_context):
global inference_files_zip_url
global msg_per_minute
global object_of_interest
print("")
print("Twin callback called with:")
print(" updateStatus: %s" % update_state)
print(" payload: %s" % payload)
data = json.loads(payload)
self.setRestartCamera = False
if "desired" in data and "inference_files_zip_url" in data["desired"]:
self.model_dst_folder = "default_model"
inference_files_zip_url = data["desired"][
"inference_files_zip_url"]
if inference_files_zip_url:
print(
"\n Setting value to %s from :: data[\"desired\"][\"all_inference_files_zip\"]"
% inference_files_zip_url)
self.setRestartCamera = get_file_zip(inference_files_zip_url,
self.model_dst_folder)
self.model_url = inference_files_zip_url
else:
print(inference_files_zip_url)
self.model_url = None
if "inference_files_zip_url" in data:
self.model_dst_folder = "default_model"
inference_files_zip_url = data["inference_files_zip_url"]
if inference_files_zip_url:
print(
"\n Setting value to %s from :: data[\"all_inference_files_zip\"]"
% inference_files_zip_url)
self.ret_flag = get_file_zip(inference_files_zip_url,
self.model_dst_folder)
#self.setRestartCamera = True
self.model_url = inference_files_zip_url
else:
print(inference_files_zip_url)
self.model_url = None
if "desired" in data and "cam_type" in data["desired"]:
cam_type = data["desired"]["cam_type"]
self.cam_type = str(cam_type)
print("Setting value to %s from :: data[desired][cam_type]" %
cam_type)
self.ret_flag = True
elif "cam_type" in data:
cam_type = data["cam_type"]
self.cam_type = str(cam_type)
print("Setting value to %s from :: data[cam_type]" % cam_type)
self.ret_flag = True
if "desired" in data and "cam_source" in data["desired"]:
cam_source = data["desired"]["cam_source"]
self.cam_source = str(cam_source)
print("Setting value to %s from :: data[desired][cam_source]" %
cam_source)
self.ret_flag = True
elif "cam_source" in data:
cam_source = data["cam_source"]
self.cam_source = str(cam_source)
print("Setting value to %s from :: data[cam_source]" % cam_source)
self.ret_flag = True
if self.cam_source:
if self.cam_type == "video_file":
print("self.cam_source %s file" % self.cam_source)
dst_folder = "sample_video"
print(
"\n Download and unzip video file to sample dir from %s" %
self.cam_source)
self.ret_flag = get_file_zip(self.cam_source, dst_folder)
#ToDo readfilename and add to dst_folder
self.cam_source = "/sample_video/video.mp4"
#self.setRestartCamera = True
else:
print(self.cam_source)
if "desired" in data and "object_of_interest" in data["desired"]:
object_of_interest = data["desired"]["object_of_interest"]
print("Setting value to %s from :: data[\"object_of_interest\"]" %
object_of_interest)
if "object_of_interest" in data:
object_of_interest = data["object_of_interest"]
print("Setting value to %s from :: data[\"object_of_interest\"]" %
object_of_interest)
if "desired" in data and "msg_per_minute" in data["desired"]:
msg_per_minute = data["desired"]["msg_per_minute"]
print("Setting value to %s from :: data[\"msg_per_minute\"]" %
msg_per_minute)
if "msg_per_minute" in data:
msg_per_minute = data["msg_per_minute"]
print("Setting value to %s from :: data[\"msg_per_minute\"]" %
msg_per_minute)
if self.ret_flag:
try:
print("setting restart inferense to True")
self.setRestartCamera = True
logger.info("Restarting inferencing")
except Exception as e:
logger.info("Got an issue during cam ON off after twin update")
logger.exception(e)
raise
def module_twin_callback(self, update_state, payload, user_context):
global inference_files_zip_url
global model_url
global label_url
global config_url
global msg_per_minute
global wait_for_minutes
global object_of_interest
print("")
print("Twin callback called with:")
print(" updateStatus: %s" % update_state)
print(" payload: %s" % payload)
data = json.loads(payload)
setRestartCamera = False
if "desired" in data and "inference_files_zip_url" in data["desired"]:
dst_folder = "twin_provided_model"
inference_files_zip_url = data["desired"][
"inference_files_zip_url"]
if inference_files_zip_url:
print(
"Setting value to %s from :: data[\"desired\"][\"all_inference_files_zip\"]"
% inference_files_zip_url)
setRestartCamera = get_file_zip(inference_files_zip_url,
dst_folder)
else:
print(inference_files_zip_url)
if "inference_files_zip_url" in data:
dst_folder = "twin_provided_model"
inference_files_zip_url = data["inference_files_zip_url"]
if inference_files_zip_url:
print(
"Setting value to %s from :: data[\"all_inference_files_zip\"]"
% inference_files_zip_url)
setRestartCamera = get_file_zip(inference_files_zip_url,
dst_folder)
else:
print(inference_files_zip_url)
if "desired" in data and "msg_per_minute" in data["desired"]:
msg_per_minute = data["desired"]["msg_per_minute"]
msg_per_minute = 60 / int(msg_per_minute)
print("Setting value to %s from :: data[\"msg_per_minute\"]" %
msg_per_minute)
if "msg_per_minute" in data:
msg_per_minute = data["msg_per_minute"]
wait_for_minutes = int(60 / int(msg_per_minute))
print("Setting value to %s from :: data[\"msg_per_minute\"]" %
msg_per_minute)
if "desired" in data and "object_of_interest" in data["desired"]:
object_of_interest = data["desired"]["object_of_interest"]
print("Setting value to %s from :: data[\"object_of_interest\"]" %
object_of_interest)
if "object_of_interest" in data:
msg_per_minute = data["object_of_interest"]
print("Setting value to %s from :: data[\"object_of_interest\"]" %
object_of_interest)
if setRestartCamera:
#
try:
logger.info("Restarting VAM to apply new model config")
self.restartInference(self.iot_camera_handle)
except Exception as e:
logger.info("Got an issue during vam ON off after twin update")
logger.exception(e)
raise
