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app.py

@@ -1,13 +1,10 @@
-# import torch
 import gradio as gr
+import torch
 from diffusers.utils import load_image
 import spaces
 from panna.pipeline import PipelineDepth2ImageV2
-# from panna import Depth2Image, DepthAnythingV2
 
-model = PipelineDepth2ImageV2()
-# model_depth = DepthAnythingV2()
-# model_image = Depth2Image()
+model = PipelineDepth2ImageV2(torch_dtype=torch.float32)
 title = ("# [Depth2Image](https://huggingface.co/stabilityai/stable-diffusion-2-depth) with [DepthAnythingV2](https://huggingface.co/depth-anything/Depth-Anything-V2-Large-hf)\n"
          "Depth2Image with depth map predicted by DepthAnything V2. The demo is part of [panna](https://github.com/abacws-abacus/panna) project.")
 example_files = []
@@ -16,22 +13,6 @@ for n in range(1, 10):
     example_files.append(f"demo{n:0>2}.jpg")
 
 
-# @spaces.GPU
-# def infer(init_image, prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps):
-#     depth = model_depth.image2depth([init_image], return_tensor=True)
-#     return model_image.text2image(
-#         [init_image],
-#         depth_maps=depth,
-#         prompt=[prompt],
-#         negative_prompt=[negative_prompt],
-#         guidance_scale=guidance_scale,
-#         num_inference_steps=num_inference_steps,
-#         height=height,
-#         width=width,
-#         seed=seed
-#     )[0]
-
-
 @spaces.GPU
 def infer(init_image, prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps):
     return model(