Fix: transformers 5.x compat, gradio 6.x, ensure_weights, sam3 access

- Remove show_api (removed in gradio 6.x)
- Add FLAX_WEIGHTS_NAME compat patch for transformers 5.x
- Add safety_checker=None to bypass Sam3 load error
- Add ensure_weights() with sentinel-file skip logic + retry
- Add hf_transfer for faster downloads
- Update requirements: transformers>=5.3.0, add av/moviepy/peft

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

diffueraser/diffueraser.py

@@ -210,7 +210,8 @@ class DiffuEraser:
             text_encoder=self.text_encoder,
             tokenizer=self.tokenizer,
             unet=self.unet_main,
-            brushnet=self.brushnet
+            brushnet=self.brushnet,
+            safety_checker=None,
         ).to(self.device, torch.float16)
         self.pipeline.scheduler = UniPCMultistepScheduler.from_config(self.pipeline.scheduler.config)
         self.pipeline.set_progress_bar_config(disable=True)

gradio_app.py

@@ -1,5 +1,8 @@
+import os
+os.environ.setdefault("HF_HUB_DISABLE_SYMLINKS_WARNING", "1")
+os.environ.setdefault("HF_HUB_ENABLE_HF_TRANSFER", "1")
 import spaces
-import torch, os, time, datetime, numpy as np, cv2
+import torch, time, datetime, numpy as np, cv2
 from PIL import Image
 import gradio as gr
 from huggingface_hub import snapshot_download
@@ -9,13 +12,41 @@ import transformers.utils
 if not hasattr(transformers.utils, "FLAX_WEIGHTS_NAME"):
     transformers.utils.FLAX_WEIGHTS_NAME = "flax_model.msgpack"
 
+def ensure_weights(repo_id, local_dir, sentinel_files, ignore_patterns=None, max_retries=5):
+    """Download repo only if sentinel files are missing; retry on network errors."""
+    import time as _time
+    # Check if already downloaded by verifying sentinel files exist
+    if all(os.path.exists(os.path.join(local_dir, f)) for f in sentinel_files):
+        print(f"[Skip] {repo_id} already present at {local_dir}")
+        return
+    os.makedirs(local_dir, exist_ok=True)
+    for attempt in range(1, max_retries + 1):
+        try:
+            snapshot_download(repo_id=repo_id, local_dir=local_dir,
+                              ignore_patterns=ignore_patterns)
+            print(f"[OK] {repo_id}")
+            return
+        except Exception as e:
+            if attempt == max_retries:
+                raise
+            print(f"[Download] {repo_id} attempt {attempt} failed: {e}\n  Retrying in 5s...")
+            _time.sleep(5)
+
 for subfolder in ["diffuEraser","stable-diffusion-v1-5","PCM_Weights","propainter","sd-vae-ft-mse"]:
     os.makedirs(os.path.join("weights", subfolder), exist_ok=True)
-snapshot_download(repo_id="lixiaowen/diffuEraser", local_dir="./weights/diffuEraser")
-snapshot_download(repo_id="stable-diffusion-v1-5/stable-diffusion-v1-5", local_dir="./weights/stable-diffusion-v1-5")
-snapshot_download(repo_id="wangfuyun/PCM_Weights", local_dir="./weights/PCM_Weights")
-snapshot_download(repo_id="camenduru/ProPainter", local_dir="./weights/propainter")
-snapshot_download(repo_id="stabilityai/sd-vae-ft-mse", local_dir="./weights/sd-vae-ft-mse")
+
+ensure_weights("lixiaowen/diffuEraser", "./weights/diffuEraser",
+               sentinel_files=["brushnet/diffusion_pytorch_model.safetensors",
+                                "unet_main/diffusion_pytorch_model.safetensors"])
+ensure_weights("stable-diffusion-v1-5/stable-diffusion-v1-5", "./weights/stable-diffusion-v1-5",
+               sentinel_files=["unet/diffusion_pytorch_model.safetensors", "model_index.json"],
+               ignore_patterns=["*.ckpt", "*.msgpack", "*non_ema*", "*.pb", "*.h5", "flax_*"])
+ensure_weights("wangfuyun/PCM_Weights", "./weights/PCM_Weights",
+               sentinel_files=["sd15/pcm_sd15_smallcfg_2step_converted.safetensors"])
+ensure_weights("camenduru/ProPainter", "./weights/propainter",
+               sentinel_files=["ProPainter.pth"])
+ensure_weights("stabilityai/sd-vae-ft-mse", "./weights/sd-vae-ft-mse",
+               sentinel_files=["diffusion_pytorch_model.safetensors"])
 
 from diffueraser.diffueraser import DiffuEraser
 from propainter.inference import Propainter, get_device
@@ -171,4 +202,4 @@ with gr.Blocks(title="DiffuEraser + SAM3 Watermark Remover") as demo:
                         inputs=[input_video, text_prompt])
     submit_btn.click(fn=infer, inputs=[input_video, text_prompt], outputs=[video_result])
 
-demo.queue().launch(show_api=True, show_error=True, ssr_mode=False)
+demo.queue().launch(show_error=True, ssr_mode=False)

requirements.txt

@@ -1,7 +1,7 @@
 torch==2.5.1
 torchvision==0.20.1
 torchaudio==2.5.1
-transformers>=4.51.0
+transformers>=5.3.0
 diffusers==0.29.2
 peft==0.13.2
 accelerate>=0.25.0
@@ -17,5 +17,6 @@ tqdm==4.66.4
 einops==0.8.0
 scipy==1.13.1
 huggingface-hub
+hf_transfer
 urllib3==2.2.2
 zipp==3.19.2