|
|
|
|
|
|
|
|
|
@@ -1,8 +1,12 @@ |
|
+import pathlib |
|
+ |
|
import numpy as np |
|
import cv2 |
|
import torch |
|
from einops import rearrange |
|
|
|
+root_dir = pathlib.Path(__file__).parents[2] |
|
+ |
|
|
|
class Network(torch.nn.Module): |
|
def __init__(self): |
|
@@ -64,7 +68,7 @@ class Network(torch.nn.Module): |
|
torch.nn.Sigmoid() |
|
) |
|
|
|
- self.load_state_dict({strKey.replace('module', 'net'): tenWeight for strKey, tenWeight in torch.load('./annotator/ckpts/network-bsds500.pth').items()}) |
|
+ self.load_state_dict({strKey.replace('module', 'net'): tenWeight for strKey, tenWeight in torch.load(f'{root_dir}/annotator/ckpts/network-bsds500.pth').items()}) |
|
# end |
|
|
|
def forward(self, tenInput): |
|
|
|
|
|
|
|
|
|
@@ -1,5 +1,7 @@ |
|
# based on https://github.com/isl-org/MiDaS |
|
|
|
+import pathlib |
|
+ |
|
import cv2 |
|
import torch |
|
import torch.nn as nn |
|
@@ -10,10 +12,11 @@ from .midas.midas_net import MidasNet |
|
from .midas.midas_net_custom import MidasNet_small |
|
from .midas.transforms import Resize, NormalizeImage, PrepareForNet |
|
|
|
+root_dir = pathlib.Path(__file__).parents[2] |
|
|
|
ISL_PATHS = { |
|
- "dpt_large": "annotator/ckpts/dpt_large-midas-2f21e586.pt", |
|
- "dpt_hybrid": "annotator/ckpts/dpt_hybrid-midas-501f0c75.pt", |
|
+ "dpt_large": f"{root_dir}/annotator/ckpts/dpt_large-midas-2f21e586.pt", |
|
+ "dpt_hybrid": f"{root_dir}/annotator/ckpts/dpt_hybrid-midas-501f0c75.pt", |
|
"midas_v21": "", |
|
"midas_v21_small": "", |
|
} |
|
|
|
|
|
|
|
|
|
@@ -1,3 +1,5 @@ |
|
+import pathlib |
|
+ |
|
import cv2 |
|
import numpy as np |
|
import torch |
|
@@ -8,8 +10,9 @@ from .models.mbv2_mlsd_tiny import MobileV2_MLSD_Tiny |
|
from .models.mbv2_mlsd_large import MobileV2_MLSD_Large |
|
from .utils import pred_lines |
|
|
|
+root_dir = pathlib.Path(__file__).parents[2] |
|
|
|
-model_path = './annotator/ckpts/mlsd_large_512_fp32.pth' |
|
+model_path = f'{root_dir}/annotator/ckpts/mlsd_large_512_fp32.pth' |
|
model = MobileV2_MLSD_Large() |
|
model.load_state_dict(torch.load(model_path), strict=True) |
|
model = model.cuda().eval() |
|
|
|
|
|
|
|
|
|
@@ -1,4 +1,5 @@ |
|
import os |
|
+import pathlib |
|
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE" |
|
|
|
import torch |
|
@@ -7,8 +8,10 @@ from . import util |
|
from .body import Body |
|
from .hand import Hand |
|
|
|
-body_estimation = Body('./annotator/ckpts/body_pose_model.pth') |
|
-hand_estimation = Hand('./annotator/ckpts/hand_pose_model.pth') |
|
+root_dir = pathlib.Path(__file__).parents[2] |
|
+ |
|
+body_estimation = Body(f'{root_dir}/annotator/ckpts/body_pose_model.pth') |
|
+hand_estimation = Hand(f'{root_dir}/annotator/ckpts/hand_pose_model.pth') |
|
|
|
|
|
def apply_openpose(oriImg, hand=False): |
|
|
|
|
|
|
|
|
|
@@ -1,9 +1,12 @@ |
|
+import pathlib |
|
+ |
|
from annotator.uniformer.mmseg.apis import init_segmentor, inference_segmentor, show_result_pyplot |
|
from annotator.uniformer.mmseg.core.evaluation import get_palette |
|
|
|
+root_dir = pathlib.Path(__file__).parents[2] |
|
|
|
-checkpoint_file = "annotator/ckpts/upernet_global_small.pth" |
|
-config_file = 'annotator/uniformer/exp/upernet_global_small/config.py' |
|
+checkpoint_file = f"{root_dir}/annotator/ckpts/upernet_global_small.pth" |
|
+config_file = f'{root_dir}/annotator/uniformer/exp/upernet_global_small/config.py' |
|
model = init_segmentor(config_file, checkpoint_file).cuda() |
|
|
|
|
|
|