Update src/pipelines/inpainting.py

src/pipelines/inpainting.py

@@ -1,42 +1,42 @@
-import torch
-import spaces
-import gradio as gr
-from src.util.base import *
-from src.util.params import *
-from diffusers import AutoPipelineForInpainting
+# import torch
+# import spaces
+# import gradio as gr
+# from src.util.base import *
+# from src.util.params import *
+# from diffusers import AutoPipelineForInpainting
 
-inpaint_pipe = AutoPipelineForInpainting.from_pretrained(inpaint_model_path).to(torch_device)
-# inpaint_pipe = AutoPipelineForInpainting.from_pipe(pipe).to(torch_device)
+# inpaint_pipe = AutoPipelineForInpainting.from_pretrained(inpaint_model_path).to(torch_device)
+# # inpaint_pipe = AutoPipelineForInpainting.from_pipe(pipe).to(torch_device)
 
-@spaces.GPU(enable_queue=True)
-def inpaint(dict, num_inference_steps, seed, prompt="", progress=gr.Progress()):
-    progress(0)
-    mask = dict["mask"].convert("RGB").resize((imageHeight, imageWidth))
-    init_image = dict["image"].convert("RGB").resize((imageHeight, imageWidth))
-    output = inpaint_pipe(
-        prompt=prompt,
-        image=init_image,
-        mask_image=mask,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        generator=torch.Generator().manual_seed(seed),
-    )
-    progress(1)
+# @spaces.GPU(enable_queue=True)
+# def inpaint(dict, num_inference_steps, seed, prompt="", progress=gr.Progress()):
+#     progress(0)
+#     mask = dict["mask"].convert("RGB").resize((imageHeight, imageWidth))
+#     init_image = dict["image"].convert("RGB").resize((imageHeight, imageWidth))
+#     output = inpaint_pipe(
+#         prompt=prompt,
+#         image=init_image,
+#         mask_image=mask,
+#         guidance_scale=guidance_scale,
+#         num_inference_steps=num_inference_steps,
+#         generator=torch.Generator().manual_seed(seed),
+#     )
+#     progress(1)
 
-    fname = "inpainting"
-    tab_config = {
-        "Tab": "Inpainting",
-        "Prompt": prompt,
-        "Number of Inference Steps per Image": num_inference_steps,
-        "Seed": seed,
-    }
+#     fname = "inpainting"
+#     tab_config = {
+#         "Tab": "Inpainting",
+#         "Prompt": prompt,
+#         "Number of Inference Steps per Image": num_inference_steps,
+#         "Seed": seed,
+#     }
 
-    imgs_list = []
-    imgs_list.append((output.images[0], "Inpainted Image"))
-    imgs_list.append((mask, "Mask"))
+#     imgs_list = []
+#     imgs_list.append((output.images[0], "Inpainted Image"))
+#     imgs_list.append((mask, "Mask"))
 
-    export_as_zip(imgs_list, fname, tab_config)
-    return output.images[0], f"outputs/{fname}.zip"
+#     export_as_zip(imgs_list, fname, tab_config)
+#     return output.images[0], f"outputs/{fname}.zip"
 
 
-__all__ = ["inpaint"]
+# __all__ = ["inpaint"]