Merge branch 'main' into pr/75

app.py

@@ -36,8 +36,8 @@ def predict(input_image, prompt, negative_prompt, steps, num_samples, scale, see
         depth_image = pad_image(depth_image)
         depth_image = depth_image.resize((512, 512))
         depth = np.array(depth_image.convert("L"))
+        depth = np.expand_dims(depth, 0)
         depth = depth.astype(np.float32) / 255.0
-        depth = depth[None, None]
         depth = torch.from_numpy(depth)
     init_image = input_image.convert("RGB")
     image = pad_image(init_image)  # resize to integer multiple of 32
@@ -49,8 +49,8 @@ def predict(input_image, prompt, negative_prompt, steps, num_samples, scale, see
         image=image,
         prompt=prompt,
         negative_prompt=negative_prompt,
-        depth_image=depth,
         generator=generator,
+        depth_map=depth,
         strength=strength,
         num_inference_steps=steps,
         guidance_scale=scale,
@@ -71,12 +71,12 @@ with block:
         with gr.Column():
             input_image = gr.Image(source='upload', type="pil")
             depth_image = gr.Image(
-                source='upload', type="pil", label="Depth image Optional", value=None)
+                source='upload', type="pil", label="Depth Image Optional", value=None)
             prompt = gr.Textbox(label="Prompt")
-            negative_prompt = gr.Textbox(label="Negative Pompt")
+            negative_prompt = gr.Textbox(label="Negative Prompt")
 
             run_button = gr.Button(label="Run")
-            with gr.Accordion("Advanced options", open=False):
+            with gr.Accordion("Advanced Options", open=False):
                 num_samples = gr.Slider(
                     label="Images", minimum=1, maximum=4, value=1, step=1)
                 steps = gr.Slider(label="Steps", minimum=1,
@@ -95,7 +95,7 @@ with block:
                     randomize=True,
                 )
         with gr.Column():
-            gallery = gr.Gallery(label="Generated images", show_label=False).style(
+            gallery = gr.Gallery(label="Generated Images", show_label=False).style(
                 grid=[2], height="auto")
     gr.Examples(
         examples=[