NewFit

README.md

@@ -4,8 +4,7 @@ emoji: 🥼👖👗
 colorFrom: yellow
 colorTo: pink
 sdk: gradio
-sdk_version: 6.20.0
-python_version: '3.10'
+sdk_version: 4.36.1
 app_file: ./run/gradio_ootd.py
 pinned: false
 license: cc-by-nc-sa-4.0

requirements.txt

@@ -1,17 +1,18 @@
-torch==2.8.0
-torchvision==0.23.0
-torchaudio==2.8.0
+torch==2.0.1
+torchvision==0.15.2
+torchaudio==2.0.2
 numpy==1.24.4
 scipy==1.10.1
 scikit-image==0.21.0
 opencv-python==4.7.0.72
 pillow==9.4.0
 diffusers==0.24.0
-transformers
+transformers==4.36.2
 accelerate==0.26.1
 matplotlib==3.7.4
 tqdm==4.64.1
+gradio==4.16.0
 config==0.5.1
 einops==0.7.0
 onnxruntime==1.16.2
-basicsr
+basicsr

run/gradio_ootd.py

@@ -1,50 +1,4 @@
 import spaces
-# --- compat shim: torchvision >=0.17 removed torchvision.transforms.functional_tensor,
-# which basicsr/gfpgan/facexlib still import from. Re-create it as an alias module
-# pointing at torchvision.transforms.functional (which has the same tensor-capable fns).
-import sys as _sys, types as _types
-try:
-    import torchvision.transforms.functional as _tv_functional
-    if "torchvision.transforms.functional_tensor" not in _sys.modules:
-        _functional_tensor_shim = _types.ModuleType("torchvision.transforms.functional_tensor")
-        for _name in ("rgb_to_grayscale", "adjust_brightness", "adjust_contrast",
-                      "adjust_hue", "adjust_saturation", "normalize"):
-            if hasattr(_tv_functional, _name):
-                setattr(_functional_tensor_shim, _name, getattr(_tv_functional, _name))
-        _sys.modules["torchvision.transforms.functional_tensor"] = _functional_tensor_shim
-except Exception:
-    pass
-# --- end compat shim ---
-
-
-# --- compat shim: huggingface_hub >=1.0 removed cached_download and HfFolder,
-# which diffusers==0.24.0 (and old transformers) still import. Re-inject them
-# BEFORE importing diffusers / transformers / the model.
-import huggingface_hub as _hub
-import huggingface_hub.constants as _hc
-if not hasattr(_hub, "cached_download"):
-    _hub.cached_download = _hub.hf_hub_download
-if not hasattr(_hub, "HfFolder"):
-    class _HfFolder:
-        @staticmethod
-        def get_token():
-            return _hub.get_token()
-    _hub.HfFolder = _HfFolder
-if not hasattr(_hc, "hf_cache_home"):
-    _hc.hf_cache_home = _hc.HF_HOME
-if not hasattr(_hub, "is_offline_mode"):
-    _hub.is_offline_mode = lambda: _hc.HF_HUB_OFFLINE
-# --- end hub compat shim ---
-
-
-# --- compat shim: transformers >=5.0 removed the Flax weight-name constant that
-# diffusers==0.24.0 (pipeline_utils) still imports. Re-inject it BEFORE the
-# diffusers/transformers import chain triggered by the model imports below.
-import transformers.utils as _tu
-if not hasattr(_tu, "FLAX_WEIGHTS_NAME"):
-    _tu.FLAX_WEIGHTS_NAME = "flax_model.msgpack"
-# --- end transformers compat shim ---
-
 
 import gradio as gr
 import os