| 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(), 'checkpoints/humanparsing/parsing_atr.onnx'), | |
| sess_options=session_options, providers=['CPUExecutionProvider']) | |
| self.lip_session = ort.InferenceSession(os.path.join(Path(__file__).absolute().parents[2].absolute(), 'checkpoints/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 | |