Spaces:
Configuration error
Configuration error
File size: 2,581 Bytes
5602c9a c7c6869 5602c9a c7c6869 5602c9a c7c6869 5602c9a 00b18c3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
import cv2
import numpy as np
import os
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
import onnxruntime as ort
from .onnxdet import inference_detector
from .onnxpose import inference_pose
from annotator.util import annotator_ckpts_path
class Wholebody:
def __init__(self):
device = 'cuda:0'
providers = ['CPUExecutionProvider'
] if device == 'cpu' else ['CUDAExecutionProvider']
remote_dw_pose_path = "https://huggingface.co/sxela/dwpose_ckpts/resolve/main/dw-ll_ucoco_384.onnx"
remote_yolox_path = "https://huggingface.co/sxela/dwpose_ckpts/resolve/main/yolox_l.onnx"
dw_pose_path = os.path.join(annotator_ckpts_path, "dw-ll_ucoco_384.onnx")
yolox_path = os.path.join(annotator_ckpts_path, "yolox_l.onnx")
if not os.path.exists(dw_pose_path):
from basicsr.utils.download_util import load_file_from_url
load_file_from_url(remote_dw_pose_path, model_dir=annotator_ckpts_path)
if not os.path.exists(yolox_path):
from basicsr.utils.download_util import load_file_from_url
load_file_from_url(remote_yolox_path, model_dir=annotator_ckpts_path)
onnx_det = 'annotator/ckpts/yolox_l.onnx'
onnx_pose = 'annotator/ckpts/dw-ll_ucoco_384.onnx'
self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers)
self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers)
def __call__(self, oriImg):
det_result = inference_detector(self.session_det, oriImg)
keypoints, scores = inference_pose(self.session_pose, det_result, oriImg)
keypoints_info = np.concatenate(
(keypoints, scores[..., None]), axis=-1)
# compute neck joint
neck = np.mean(keypoints_info[:, [5, 6]], axis=1)
# neck score when visualizing pred
neck[:, 2:4] = np.logical_and(
keypoints_info[:, 5, 2:4] > 0.3,
keypoints_info[:, 6, 2:4] > 0.3).astype(int)
new_keypoints_info = np.insert(
keypoints_info, 17, neck, axis=1)
mmpose_idx = [
17, 6, 8, 10, 7, 9, 12, 14, 16, 13, 15, 2, 1, 4, 3
]
openpose_idx = [
1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17
]
new_keypoints_info[:, openpose_idx] = \
new_keypoints_info[:, mmpose_idx]
keypoints_info = new_keypoints_info
keypoints, scores = keypoints_info[
..., :2], keypoints_info[..., 2]
return keypoints, scores |