Update app.py

app.py

@@ -106,61 +106,13 @@ def sample(
     return video_path, seed
 
 
-def resize_image(image, output_size=(1024, 576)):
-    # Calculate aspect ratios
-    target_aspect = output_size[0] / output_size[1]  # Aspect ratio of the desired size
-    image_aspect = image.width / image.height  # Aspect ratio of the original image
-
-    # Resize then crop if the original image is larger
-    if image_aspect > target_aspect:
-        # Resize the image to match the target height, maintaining aspect ratio
-        new_height = output_size[1]
-        new_width = int(new_height * image_aspect)
-        resized_image = image.resize((new_width, new_height), Image.LANCZOS)
-        # Calculate coordinates for cropping
-        left = (new_width - output_size[0]) / 2
-        top = 0
-        right = (new_width + output_size[0]) / 2
-        bottom = output_size[1]
-    else:
-        # Resize the image to match the target width, maintaining aspect ratio
-        new_width = output_size[0]
-        new_height = int(new_width / image_aspect)
-        resized_image = image.resize((new_width, new_height), Image.LANCZOS)
-        # Calculate coordinates for cropping
-        left = 0
-        top = (new_height - output_size[1]) / 2
-        right = output_size[0]
-        bottom = (new_height + output_size[1]) / 2
-
-    # Crop the image
-    cropped_image = resized_image.crop((left, top, right, bottom))
-    return cropped_image
-
-
 with gr.Blocks() as demo:
-    gr.Markdown(
-        """
-                # [AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning](https://arxiv.org/abs/2402.00769)
-                Fu-Yun Wang, Zhaoyang Huang (*Corresponding Author), Xiaoyu Shi, Weikang Bian, Guanglu Song, Yu Liu, Hongsheng Li (*Corresponding Author)<br>
-                
-                [arXiv Report](https://arxiv.org/abs/2402.00769) | [Project Page](https://animatelcm.github.io/) | [Github](https://github.com/G-U-N/AnimateLCM) | [Civitai](https://civitai.com/models/290375/animatelcm-fast-video-generation) | [Replicate](https://replicate.com/camenduru/animate-lcm)
-                
-                Related Models:
-                [AnimateLCM-t2v](https://huggingface.co/wangfuyun/AnimateLCM): Personalized Text-to-Video Generation
-                [AnimateLCM-SVD-xt](https://huggingface.co/wangfuyun/AnimateLCM-SVD-xt): General Image-to-Video Generation
-                [AnimateLCM-i2v](https://huggingface.co/wangfuyun/AnimateLCM-I2V): Personalized Image-to-Video Generation
-                """
-    )
     with gr.Row():
         with gr.Column():
             image = gr.Image(label="Upload your image", type="pil")
             generate_btn = gr.Button("Generate")
         video = gr.Video()
-    with gr.Accordion("Advanced options", open=False):
-        safetensors_dropdown = gr.Dropdown(
-            label="Choose Safetensors", choices=get_safetensors_files()
-        )
+
         seed = gr.Slider(
             label="Seed",
             value=42,
@@ -184,18 +136,22 @@ with gr.Blocks() as demo:
             minimum=5,
             maximum=30,
         )
+        # note: we want something that is close to 16:9 (1.7777)
+        # 576 / 320 = 1.8
+        #  448 / 256 = 1.75
         width = gr.Slider(
             label="Width of input image",
             info="It should be divisible by 64",
-            value=1024,
-            minimum=576,
+            value=576, # 256, 320, 384, 448
+            minimum=256,
             maximum=2048,
+            step=64,
         )
         height = gr.Slider(
             label="Height of input image",
             info="It should be divisible by 64",
-            value=576,
-            minimum=320,
+            value=320, # 256, 320, 384, 448
+            minimum=256,
             maximum=1152,
         )
         max_guidance_scale = gr.Slider(
@@ -221,7 +177,6 @@ with gr.Blocks() as demo:
             step=1,
         )
 
-    image.upload(fn=resize_image, inputs=image, outputs=image, queue=False)
     generate_btn.click(
         fn=sample,
         inputs=[
@@ -239,21 +194,6 @@ with gr.Blocks() as demo:
         outputs=[video, seed],
         api_name="video",
     )
-    safetensors_dropdown.change(fn=model_select, inputs=safetensors_dropdown)
-
-    gr.Examples(
-        examples=[
-            ["test_imgs/ai-generated-8496135_1280.jpg"],
-            ["test_imgs/dog-7396912_1280.jpg"],
-            ["test_imgs/ship-7833921_1280.jpg"],
-            ["test_imgs/girl-4898696_1280.jpg"],
-            ["test_imgs/power-station-6579092_1280.jpg"]
-        ],
-        inputs=[image],
-        outputs=[video, seed],
-        fn=sample,
-        cache_examples=True,
-    )
 
 if __name__ == "__main__":
     demo.queue()