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import pdb
from pathlib import Path
import sys
import os
import onnxruntime as ort
PROJECT_ROOT = Path(__file__).absolute().parents[0].absolute()
sys.path.insert(0, str(PROJECT_ROOT))
from parsing_api import onnx_inference
import torch
class Parsing:
def __init__(self, gpu_id: int):
# self.gpu_id = gpu_id
# torch.cuda.set_device(gpu_id)
session_options = ort.SessionOptions()
session_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
session_options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL
# session_options.add_session_config_entry('gpu_id', str(gpu_id))
self.session = ort.InferenceSession(os.path.join(Path(__file__).absolute().parents[2].absolute(), 'ckpt/humanparsing/parsing_atr.onnx'),
sess_options=session_options, providers=['CPUExecutionProvider'])
self.lip_session = ort.InferenceSession(os.path.join(Path(__file__).absolute().parents[2].absolute(), 'ckpt/humanparsing/parsing_lip.onnx'),
sess_options=session_options, providers=['CPUExecutionProvider'])
def __call__(self, input_image):
# torch.cuda.set_device(self.gpu_id)
parsed_image, face_mask = onnx_inference(self.session, self.lip_session, input_image)
return parsed_image, face_mask
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