INNER CODE UNIT · Python

image_vq_id

FoundationVision/Liquid · evaluation/app.py:266

        image_vq_id = torch.cat(pred_tokens,dim=1)-ori_vocabe_size
        image_vq_id = torch.clamp(image_vq_id, min=0, max=8191)
        
        generated_image_list = []
        for index, generate_id in enumerate(image_vq_id):
            rec_img = image_tokenizer.pil_from_img_toks(generate_id)
            generated_image_list.append(rec_img)
            # rec_img.save('{}/{}.jpg'.format(image_save_pth,str(idx)))

        torch.cuda.empty_cache()
         # yield gr.Image(value=generated_image_list[0], label="Generated Image", show_download_button=True) 
        yield show_gallery(generated_image_list)

def bot_streaming_T2T(message, history,temperature):
    print(message)
    global stop_flag
    stop_flag = True
    time.sleep(0.2)

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