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app.py

@@ -1,10 +1,13 @@
+import torch
 import gradio as gr
 from diffusers.utils import load_image
 import spaces
-from panna.pipeline import PipelineDepth2ImageV2
+# from panna.pipeline import PipelineDepth2ImageV2
+from panna import Depth2Image, DepthAnythingV2
 
-
-model = PipelineDepth2ImageV2()
+# model = PipelineDepth2ImageV2()
+model_depth = DepthAnythingV2("depth-anything/Depth-Anything-V2-Large-hf", torch_dtype=torch.float32)
+model_image = Depth2Image("stabilityai/stable-diffusion-2-depth")
 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 = []
@@ -15,16 +18,32 @@ for n in range(1, 10):
 
 @spaces.GPU
 def infer(init_image, prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps):
-    return model(
-        init_image,
-        prompt=prompt,
-        negative_prompt=negative_prompt,
+    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(
+#         init_image,
+#         prompt=prompt,
+#         negative_prompt=negative_prompt,
+#         guidance_scale=guidance_scale,
+#         num_inference_steps=num_inference_steps,
+#         height=height,
+#         width=width,
+#         seed=seed
+#     )
 
 
 with gr.Blocks() as demo: