Upload folder using huggingface_hub

.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 Other_dependencies/mp_models/face_landmarker_v2_with_blendshapes.task filter=lfs diff=lfs merge=lfs -text
+Other_dependencies/DLIB_landmark_det/shape_predictor_68_face_landmarks.dat filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -6,24 +6,14 @@ checkpoints
 
 
 
-#face parsing model (segmentation) Done
-Other_dependencies/face_parsing/79999_iter.pth
 
 
 
 
-# Expression model (For quantitative analysis only)  Not used
-Other_dependencies/face_recon/epoch_latest.pth
-eval_tool/Deep3DFaceRecon_pytorch_edit/BFM/*.mat
-
-# Arcface model 
-Other_dependencies/arcface/model_ir_se50.pth
 
 # pose model (For quantitative analysis only)
 Other_dependencies/Hopenet_pose/hopenet_robust_alpha1.pkl
 
-# Landmark detection model 
-Other_dependencies/DLIB_landmark_det/shape_predictor_68_face_landmarks.dat
 
 # Qantitative results
 Quantitative_Analysis/*
@@ -69,7 +59,6 @@ ttt*
 
 
 *.pt
-*.pth
 *.ckpt
 
 

Other_dependencies/DLIB_landmark_det/shape_predictor_68_face_landmarks.dat

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbdc2cb80eb9aa7a758672cbfdda32ba6300efe9b6e6c7a299ff7e736b11b92f
+size 99693937

Other_dependencies/arcface/model_ir_se50.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a035c768259b98ab1ce0e646312f48b9e1e218197a0f80ac6765e88f8b6ddf28
+size 175367323

Other_dependencies/face_parsing/79999_iter.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:468e13ca13a9b43cc0881a9f99083a430e9c0a38abd935431d1c28ee94b26567
+size 53289463

README.md

@@ -27,11 +27,13 @@ conda activate unibio
 sh setup.sh
 ```
 
+<small>*Tip*: If you encounter issues installing `dlib`, you can try: `pip install --only-binary=:all: dlib-bin==19.24.6`</small>
 
 ### 2. Download pre-trained weight
 Download pre-trained checkpoints via `python download_checkpoints.py`
 
 
+<small>*Tip*: If you have trouble accessing Hugging Face (e.g., in mainland China), you can firstly set the mirror endpoint: `export HF_ENDPOINT=https://hf-mirror.com`</small>
 
 
 ## Inference

ldm/models/diffusion/misc_4ddpm.py

@@ -39,7 +39,6 @@ from torch.distributed.optim import ZeroRedundancyOptimizer
 from src.Face_models.encoders.model_irse import Backbone
 import dlib
 from eval_tool.lpips.lpips import LPIPS
-import wandb
 from PIL import Image
 import argparse
 from contextlib import nullcontext

requirements.txt

@@ -11,7 +11,6 @@ face_alignment==1.4.1
 ftfy==6.0.3
 glfw==2.7.0
 imageio==2.14.1
-invisible_watermark==0.2.0
 kornia==0.6.0
 matplotlib==3.7.5
 more_itertools==10.5.0
@@ -34,7 +33,6 @@ setuptools==59.5.0
 scikit-image==0.20.0
 streamlit==0.73.1
 tqdm==4.66.5
-trimesh==4.4.9
 typing_extensions==4.12.2
-wandb==0.18.1
 torchmetrics==0.6.0
+mediapipe==0.10.21

util_and_constant.py

@@ -182,7 +182,7 @@ def path_img_2_path_mask( path_img, check_mask_exists = 1 , reuse_if_exists = Tr
     return path_mask
 
 from my_py_lib.torchModuleName_util import *
-if 1:
+if 0:
     #-------------------- terminal color (only for exceptions/logging/warnings)
     import sys; from IPython.core.ultratb import ColorTB; sys.excepthook = ColorTB()
     class _color:  # ANSI escape