Pull request (Debug checkbox) from magic-research#28

demo/animate.py

@@ -125,7 +125,7 @@ def __init__(self, config="configs/prompts/animation.yaml") -> None:
 
         print("Initialization Done!")
 
-    def __call__(self, source_image, motion_sequence, random_seed, step, guidance_scale, size=512):
+    def __call__(self, source_image, motion_sequence, random_seed, step, guidance_scale, debug, size=512):
             prompt = n_prompt = ""
             random_seed = int(random_seed)
             step = int(step)
@@ -171,17 +171,17 @@ def __call__(self, source_image, motion_sequence, random_seed, step, guidance_sc
                 source_image             = source_image,
             ).videos
 
-            source_images = np.array([source_image] * original_length)
-            source_images = rearrange(torch.from_numpy(source_images), "t h w c -> 1 c t h w") / 255.0
-            samples_per_video.append(source_images)
-
-            control = control / 255.0
-            control = rearrange(control, "t h w c -> 1 c t h w")
-            control = torch.from_numpy(control)
-            samples_per_video.append(control[:, :, :original_length])
+            if debug:
+              source_images = np.array([source_image] * original_length)
+              source_images = rearrange(torch.from_numpy(source_images), "t h w c -> 1 c t h w") / 255.0
+              samples_per_video.append(source_images)
+
+              control = control / 255.0
+              control = rearrange(control, "t h w c -> 1 c t h w")
+              control = torch.from_numpy(control)
+              samples_per_video.append(control[:, :, :original_length])
 
             samples_per_video.append(sample[:, :, :original_length])
-
             samples_per_video = torch.cat(samples_per_video)
 
             time_str = datetime.datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
@@ -192,4 +192,4 @@ def __call__(self, source_image, motion_sequence, random_seed, step, guidance_sc
             save_videos_grid(samples_per_video, animation_path)
 
             return animation_path
-
+

demo/gradio_animate.py

@@ -18,8 +18,8 @@
 
 animator = MagicAnimate()
 
-def animate(reference_image, motion_sequence_state, seed, steps, guidance_scale):
-    return animator(reference_image, motion_sequence_state, seed, steps, guidance_scale)
+def animate(reference_image, motion_sequence_state, seed, steps, guidance_scale, debug):
+    return animator(reference_image, motion_sequence_state, seed, steps, guidance_scale, debug)
 
 with gr.Blocks() as demo:
 
@@ -49,6 +49,7 @@ def animate(reference_image, motion_sequence_state, seed, steps, guidance_scale)
             random_seed         = gr.Textbox(label="Random seed", value=1, info="default: -1")
             sampling_steps      = gr.Textbox(label="Sampling steps", value=25, info="default: 25")
             guidance_scale      = gr.Textbox(label="Guidance scale", value=7.5, info="default: 7.5")
+            debug               = gr.Checkbox(label="Debug", value=True)
             submit              = gr.Button("Animate")
 
     def read_video(video):
@@ -74,7 +75,7 @@ def read_image(image, size=512):
     # when the `submit` button is clicked
     submit.click(
         animate,
-        [reference_image, motion_sequence, random_seed, sampling_steps, guidance_scale], 
+        [reference_image, motion_sequence, random_seed, sampling_steps, guidance_scale, debug], 
         animation
     )
 
@@ -94,4 +95,4 @@ def read_image(image, size=512):
     )
 
 
-demo.launch(share=False)
+demo.launch(share=True)

demo/gradio_animate_dist.py

@@ -10,31 +10,16 @@
 # its affiliates is strictly prohibited.
 import argparse
 import imageio
-import os, datetime
 import numpy as np
 import gradio as gr
 from PIL import Image
-from subprocess import PIPE, run
 
-os.makedirs("./demo/tmp", exist_ok=True)
-savedir = f"demo/outputs"
-os.makedirs(savedir, exist_ok=True)
+from demo.animate import MagicAnimate
 
-def animate(reference_image, motion_sequence, seed, steps, guidance_scale):
-    time_str = datetime.datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
-    animation_path = f"{savedir}/{time_str}.mp4"
-    save_path = "./demo/tmp/input_reference_image.png"
-    Image.fromarray(reference_image).save(save_path)
-    command = "python -m demo.animate_dist --reference_image {} --motion_sequence {} --random_seed {} --step {} --guidance_scale {} --save_path {}".format(
-        save_path,
-        motion_sequence,
-        seed,
-        steps,
-        guidance_scale,
-        animation_path
-    )
-    run(command, stdout=PIPE, stderr=PIPE, universal_newlines=True, shell=True)
-    return animation_path
+animator = MagicAnimate()
+
+def animate(reference_image, motion_sequence_state, seed, steps, guidance_scale, debug):
+    return animator(reference_image, motion_sequence_state, seed, steps, guidance_scale, debug)
 
 with gr.Blocks() as demo:
 
@@ -64,23 +49,17 @@ def animate(reference_image, motion_sequence, seed, steps, guidance_scale):
             random_seed         = gr.Textbox(label="Random seed", value=1, info="default: -1")
             sampling_steps      = gr.Textbox(label="Sampling steps", value=25, info="default: 25")
             guidance_scale      = gr.Textbox(label="Guidance scale", value=7.5, info="default: 7.5")
+            debug               = gr.Checkbox(label="Debug", value=True)
             submit              = gr.Button("Animate")
 
-    def read_video(video, size=512):
-        size = int(size)
+    def read_video(video):
         reader = imageio.get_reader(video)
-        # fps = reader.get_meta_data()['fps']
-        frames = []
-        for img in reader:
-            frames.append(np.array(Image.fromarray(img).resize((size, size))))
-        save_path = "./demo/tmp/input_motion_sequence.mp4"
-        imageio.mimwrite(save_path, frames, fps=25)
-        return save_path
+        fps = reader.get_meta_data()['fps']
+        return video
 
     def read_image(image, size=512):
-        img = np.array(Image.fromarray(image).resize((size, size)))
-        return img
-
+        return np.array(Image.fromarray(image).resize((size, size)))
+
     # when user uploads a new video
     motion_sequence.upload(
         read_video,
@@ -96,15 +75,15 @@ def read_image(image, size=512):
     # when the `submit` button is clicked
     submit.click(
         animate,
-        [reference_image, motion_sequence, random_seed, sampling_steps, guidance_scale], 
+        [reference_image, motion_sequence, random_seed, sampling_steps, guidance_scale, debug], 
         animation
     )
 
     # Examples
     gr.Markdown("## Examples")
     gr.Examples(
         examples=[
-            ["inputs/applications/source_image/monalisa.png", "inputs/applications/driving/densepose/running.mp4"], 
+            ["inputs/applications/source_image/monalisa.png", "inputs/applications/driving/densepose/running.mp4"],
             ["inputs/applications/source_image/demo4.png", "inputs/applications/driving/densepose/demo4.mp4"],
             ["inputs/applications/source_image/0002.png", "inputs/applications/driving/densepose/demo4.mp4"],
             ["inputs/applications/source_image/dalle2.jpeg", "inputs/applications/driving/densepose/running2.mp4"],
@@ -115,5 +94,5 @@ def read_image(image, size=512):
         outputs=animation,
     )
 
-demo.queue(max_size=10)
-demo.launch(share=True)
+
+demo.launch(share=True)