Update app.py

app.py

@@ -24,6 +24,8 @@ sys.path.append('./CLIP')
 sys.path.append('./guided-diffusion')
 import clip
 from guided_diffusion.script_util import create_model_and_diffusion, model_and_diffusion_defaults
+import numpy as np
+import imageio
 # Model settings
 model_config = model_and_diffusion_defaults()
 model_config.update({
@@ -60,6 +62,7 @@ def spherical_dist_loss(x, y):
     return (x - y).norm(dim=-1).div(2).arcsin().pow(2).mul(2)
     
 def inference(text):
+    all_frames = []
     prompt = text
     batch_size = 1
     clip_guidance_scale = 2750
@@ -103,19 +106,24 @@ def inference(text):
     
     for i, sample in enumerate(samples):
         cur_t -= 1
-        if i % 100 == 0 or cur_t == -1:
+        if i % 1 == 0 or cur_t == -1:
             print()
             for j, image in enumerate(sample['pred_xstart']):
-                filename = f'progress_{j:05}.png'
-                TF.to_pil_image(image.add(1).div(2).clamp(0, 1)).save(filename)
+                #filename = f'progress_{j:05}.png'
+                img = TF.to_pil_image(image.add(1).div(2).clamp(0, 1))
+                all_frames.append(img)
                 tqdm.write(f'Step {i}, output {j}:')
                 #display.display(display.Image(filename))
-    return 'progress_00000.png'
+    writer = imageio.get_writer('video.mp4', fps=20)
+    for im in all_frames:
+        writer.append_data(np.array(im))
+    writer.close()
+    return img, 'video.mp4'
     
 title = "CLIP Guided Diffusion"
 description = "Gradio demo for CLIP Guided Diffusion. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
 article = "<p style='text-align: center'>By Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). It uses OpenAI's 256x256 unconditional ImageNet diffusion model (https://github.com/openai/guided-diffusion) together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images. | <a href='https://colab.research.google.com/drive/1ED6_MYVXTApBHzQObUPaaMolgf9hZOOF' target='_blank'>Colab</a></p>"
 
-iface = gr.Interface(inference, inputs="text", outputs="image", title=title, description=description, article=article, examples=[["coral reef city by artistation artists"]],
+iface = gr.Interface(inference, inputs="text", outputs=["image","video"], title=title, description=description, article=article, examples=[["coral reef city by artistation artists"]],
     enable_queue=True)
 iface.launch()