gif

app.py

@@ -237,19 +237,16 @@ def infer(
     to_pil = ToPILImage()
     pil_images = [to_pil(img) for img in samples]
 
-    # Get the first and last images
     first_image = pil_images[0]
     last_image = pil_images[-1]
 
-    # Create an animated GIF from all the PIL images
-    # gif_buffer = io.BytesIO()
-    # # duration: adjust duration (ms) between frames as needed
-    # pil_images[0].save(gif_buffer, format="GIF", save_all=True, append_images=pil_images[1:], duration=10, loop=0)
-    # gif_buffer.seek(0)
-    # gif_bytes = gif_buffer.read()
+    gif_buffer = io.BytesIO()
+    pil_images[0].save(gif_buffer, format="GIF", save_all=True, append_images=pil_images[1:], duration=10, loop=0)
+    gif_buffer.seek(0)
+    gif_bytes = gif_buffer.read()
 
-    # return first_image, last_image, gif_bytes, seed
-    return first_image, last_image, seed
+    return first_image, last_image, gif_bytes, seed
+    # return first_image, last_image, seed
 
 
 # examples = [
@@ -297,7 +294,7 @@ with gr.Blocks(css=css) as demo:
         # Create separate outputs for the first image, last image, and the animated GIF
         first_image_output = gr.Image(label="Image if the first prompt", show_label=True)
         last_image_output = gr.Image(label="Image if the second prompt", show_label=True)
-        # gif_output = gr.Image(label="Linear interpolation", show_label=True)
+        gif_output = gr.Image(label="Linear interpolation", show_label=True)
 
         with gr.Accordion("Advanced Settings", open=False):
             seed = gr.Slider(
@@ -324,7 +321,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=10,  # Replace with defaults that work for your model
+                    value=50,  # Replace with defaults that work for your model
                 )
             with gr.Row():
                 num_of_interpolation = gr.Slider(
@@ -348,89 +345,10 @@ with gr.Blocks(css=css) as demo:
             num_inference_steps,
             num_of_interpolation,
         ],
-        # outputs=[first_image_output, last_image_output, gif_output, seed],
-        outputs=[first_image_output, last_image_output, seed],
+        outputs=[first_image_output, last_image_output, gif_output, seed],
+        # outputs=[first_image_output, last_image_output, seed],
     )
 
-# with gr.Blocks(css=css) as demo:
-#     with gr.Column(elem_id="col-container"):
-#         gr.Markdown(" # CrossFlow")
-#         gr.Markdown(" CrossFlow directly transforms text representations into images for text-to-image generation, enabling interpolation in the input text latent space.")
-
-#         with gr.Row():
-#             prompt1 = gr.Text(
-#                 label="Prompt_1",
-#                 show_label=False,
-#                 max_lines=1,
-#                 placeholder="Enter your prompt for the first image",
-#                 container=False,
-#             )
-        
-#         with gr.Row():
-#             prompt2 = gr.Text(
-#                 label="Prompt_2",
-#                 show_label=False,
-#                 max_lines=1,
-#                 placeholder="Enter your prompt for the second image",
-#                 container=False,
-#             )
-
-#         with gr.Row():
-#             run_button = gr.Button("Run", scale=0, variant="primary")
-
-#         result = gr.Image(label="Result", show_label=False)
-
-#         with gr.Accordion("Advanced Settings", open=False):
-#             seed = gr.Slider(
-#                 label="Seed",
-#                 minimum=0,
-#                 maximum=MAX_SEED,
-#                 step=1,
-#                 value=0,
-#             )
-
-#             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
-#             with gr.Row():
-#                 guidance_scale = gr.Slider(
-#                     label="Guidance scale",
-#                     minimum=0.0,
-#                     maximum=10.0,
-#                     step=0.1,
-#                     value=7.0,  # Replace with defaults that work for your model
-#                 )
-#             with gr.Row():
-#                 num_inference_steps = gr.Slider(
-#                     label="Number of inference steps - 50 inference steps are recommended; but you can reduce to 20 if the demo fails.",
-#                     minimum=1,
-#                     maximum=50,
-#                     step=1,
-#                     value=50,  # Replace with defaults that work for your model
-#                 )
-#             with gr.Row():
-#                 num_of_interpolation = gr.Slider(
-#                     label="Number of images for interpolation - More images yield smoother transitions but require more resources and may fail.",
-#                     minimum=5,
-#                     maximum=50,
-#                     step=1,
-#                     value=10,  # Replace with defaults that work for your model
-#                 )
-
-#         gr.Examples(examples=examples, inputs=[prompt1, prompt2])
-#     gr.on(
-#         triggers=[run_button.click, prompt1.submit, prompt2.submit],
-#         fn=infer,
-#         inputs=[
-#             prompt1,
-#             prompt2,
-#             seed,
-#             randomize_seed,
-#             guidance_scale,
-#             num_inference_steps,
-#             num_of_interpolation,
-#         ],
-#         outputs=[result, seed],
-#     )
 
 if __name__ == "__main__":
     demo.launch()