Update app.py

app.py

@@ -202,6 +202,7 @@ def inference(text):
                 for k, image in enumerate(sample['pred_xstart']):
                     #filename = f'progress_{i * batch_size + k:05}.png'
                     img = TF.to_pil_image(image.add(1).div(2).clamp(0, 1))
+                    all_frames.append(img)
                     tqdm.write(f'Batch {i}, step {j}, output {k}:')
                     #display.display(display.Image(filename))
     writer = imageio.get_writer('video.mp4', fps=20)
@@ -212,7 +213,7 @@ def inference(text):
     
 title = "CLIP Guided Diffusion HQ"
 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>"
+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/12a_Wrfi2_gwwAuN3VvMTwVMz9TfqctNj' target='_blank'>Colab</a></p>"
 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()