feat generate image 逻辑补充

This commit is contained in:
zhouchengrong
2024-04-17 17:37:51 +08:00
parent c9b407b2a4
commit 5ed53a1e7c

View File

@@ -47,6 +47,9 @@ class GenerateImage:
self.batch_size = 1
self.category = request_data.category
self.index = 0
self.generate_data = {'tasks_id': self.tasks_id, 'status': 'PENDING', 'message': "pending", 'data': ''}
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
self.redis_client.expire(self.tasks_id, 600)
def get_image(self, image_url):
# Get data of an object.
@@ -60,24 +63,23 @@ class GenerateImage:
image_cv2 = np.random.randint(0, 256, (1024, 1024, 3), dtype=np.uint8)
return image_cv2
def __call__(self, *args, **kwargs):
self.generate_data = json.dumps({'status': 'PENDING', 'message': "pending", 'data': ''})
self.redis_client.set(self.tasks_id, self.generate_data)
self.redis_client.expire(self.tasks_id, 600)
def callback(self, result, error):
if error:
generate_data = json.dumps({'status': 'FAILURE', 'message': f"{error}", 'data': f"{error}"})
self.redis_client.set(self.tasks_id, generate_data)
self.generate_data['status'] = "FAILURE"
self.generate_data['message'] = str(error)
self.generate_data['data'] = str(error)
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
else:
image_result = result.as_numpy("generated_image")[0]
image_url = upload_png_sd(image_result, user_id=self.user_id, category=f"{self.category}", object_name=f"{self.tasks_id}.png")
generate_data = json.dumps({'status': 'SUCCESS', 'message': 'success', 'data': f'{image_url}'})
self.redis_client.set(self.tasks_id, generate_data)
self.generate_data['status'] = "SUCCESS"
self.generate_data['message'] = "success"
self.generate_data['data'] = str(image_url)
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
def read_tasks_status(self):
status_data = json.loads(self.redis_client.get(self.tasks_id))
return status_data
status_data = self.redis_client.get(self.tasks_id)
return json.loads(status_data), status_data
def infer(self, inputs):
return self.grpc_client.async_infer(
@@ -87,45 +89,53 @@ class GenerateImage:
)
def get_result(self):
prompts = [self.prompt] * self.batch_size
modes = [self.mode] * self.batch_size
images = [self.image.astype(np.float16)] * self.batch_size
try:
prompts = [self.prompt] * self.batch_size
modes = [self.mode] * self.batch_size
images = [self.image.astype(np.float16)] * self.batch_size
text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
mode_obj = np.array(modes, dtype="object").reshape((-1, 1))
image_obj = np.array(images, dtype=np.float16).reshape((-1, 1024, 1024, 3))
text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
mode_obj = np.array(modes, dtype="object").reshape((-1, 1))
image_obj = np.array(images, dtype=np.float16).reshape((-1, 1024, 1024, 3))
input_text = grpcclient.InferInput("prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_image = grpcclient.InferInput("input_image", image_obj.shape, "FP16")
input_mode = grpcclient.InferInput("mode", mode_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_text = grpcclient.InferInput("prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_image = grpcclient.InferInput("input_image", image_obj.shape, "FP16")
input_mode = grpcclient.InferInput("mode", mode_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_text.set_data_from_numpy(text_obj)
input_image.set_data_from_numpy(image_obj)
input_mode.set_data_from_numpy(mode_obj)
input_text.set_data_from_numpy(text_obj)
input_image.set_data_from_numpy(image_obj)
input_mode.set_data_from_numpy(mode_obj)
inputs = [input_text, input_image, input_mode]
ctx = self.infer(inputs)
time_out = 60
while time_out > 0:
generate_data = self.read_tasks_status()
if generate_data['status'] in ["REVOKED", "FAILURE"]:
ctx.cancel()
self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=json.dumps(generate_data))
logger.info(f" [x] Sent {json.dumps(generate_data, indent=4)}")
break
elif generate_data['status'] == "SUCCESS":
self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=json.dumps(generate_data))
logger.info(f" [x] Sent {json.dumps(generate_data, indent=4)}")
break
time_out -= 1
time.sleep(0.1)
return self.read_tasks_status()
inputs = [input_text, input_image, input_mode]
ctx = self.infer(inputs)
time_out = 60
generate_data = None
while time_out > 0:
generate_data, _ = self.read_tasks_status()
if generate_data['status'] in ["REVOKED", "FAILURE"]:
ctx.cancel()
break
elif generate_data['status'] == "SUCCESS":
break
time_out -= 1
time.sleep(0.1)
return generate_data
except Exception as e:
self.generate_data['status'] = "FAILURE"
self.generate_data['message'] = "failure"
self.generate_data['data'] = str(e)
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
raise Exception(str(e))
finally:
dict_generate_data, str_generate_data = self.read_tasks_status()
self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=str_generate_data)
logger.info(f" [x] Sent {json.dumps(dict_generate_data, indent=4)}")
def infer_cancel(tasks_id):
redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True)
data = {'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'}
generate_data = json.dumps({'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'})
data = {'tasks_id': tasks_id, 'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'}
generate_data = json.dumps(data)
redis_client.set(tasks_id, generate_data)
return data