| 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 |
|
|
