Update app.py

app.py

@@ -1,141 +1,7 @@
-import os
-import sys
 
-#import numpy as np
 import streamlit as st
-#from PIL import Image
-
-# import clip
-
-
-# sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
-# import gradio as gr
-# from dalle.models import Dalle
-# from dalle.utils.utils import clip_score, set_seed
-
-
-device = "cpu"
-# model = Dalle.from_pretrained("minDALL-E/1.3B")  # This will automatically download the pretrained model.
-# model.to(device=device)
-
-# model_clip, preprocess_clip = clip.load("ViT-B/32", device=device)
-# model_clip.to(device=device)
-
-
-# def sample(prompt):
-#     # Sampling
-#     images = (
-#         model.sampling(prompt=prompt, top_k=256, top_p=None, softmax_temperature=1.0, num_candidates=3, device=device)
-#         .cpu()
-#         .numpy()
-#     )
-#     images = np.transpose(images, (0, 2, 3, 1))
-
-#     # CLIP Re-ranking
-#     rank = clip_score(
-#         prompt=prompt, images=images, model_clip=model_clip, preprocess_clip=preprocess_clip, device=device
-#     )
-
-#     # Save images
-#     images = images[rank]
-#     # print(rank, images.shape)
-#     pil_images = []
-#     for i in range(len(images)):
-#         im = Image.fromarray((images[i] * 255).astype(np.uint8))
-#         pil_images.append(im)
-
-#     # im = Image.fromarray((images[0] * 255).astype(np.uint8))
-#     return pil_images
-
-
-# title = "Interactive demo: ImageGPT"
-# description = "Demo for OpenAI's ImageGPT: Generative Pretraining from Pixels. To use it, simply upload an image or use the example image below and click 'submit'. Results will show up in a few seconds."
-# article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.10282'>ImageGPT: Generative Pretraining from Pixels</a> | <a href='https://openai.com/blog/image-gpt/'>Official blog</a></p>"
-
-# iface = gr.Interface(
-#     fn=sample,
-#     inputs=[gr.inputs.Textbox(label="What would you like to see?")],
-#     outputs=gr.outputs.Image(type="pil", label="Model input + completions"),
-#     title=title,
-#     description=description,
-#     article=article,
-#     #examples=examples,
-#     enable_queue=True,
-# )
-# iface.launch(debug=True)
-
-#!/usr/bin/env python
-# coding: utf-8
-
-
-st.sidebar.markdown(
-    """
-<style>
-.aligncenter {
-    text-align: center;
-}
-</style>
-<p class="aligncenter">
-    <img src="https://raw.githubusercontent.com/borisdayma/dalle-mini/main/img/logo.png"/>
-</p>
-""",
-    unsafe_allow_html=True,
-)
-st.sidebar.markdown(
-    """
-___
-<p style='text-align: center'>
-DALL·E mini is an AI model that generates images from any prompt you give!
-</p>
-
-<p style='text-align: center'>
-Created by Boris Dayma et al. 2021
-<br/>
-<a href="https://github.com/borisdayma/dalle-mini" target="_blank">GitHub</a> | <a href="https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA" target="_blank">Project Report</a>
-</p>
-        """,
-    unsafe_allow_html=True,
-)
 
 st.header("DALL·E mini")
 st.subheader("Generate images from text")
 
 prompt = st.text_input("What do you want to see?")
-
-DEBUG = False
-# if prompt != "":
-#     container = st.empty()
-#     container.markdown(
-#         f"""
-#         <style> p {{ margin:0 }} div {{ margin:0 }} </style>
-#         <div data-stale="false" class="element-container css-1e5imcs e1tzin5v1">
-#         <div class="stAlert">
-#         <div role="alert" data-baseweb="notification" class="st-ae st-af st-ag st-ah st-ai st-aj st-ak st-g3 st-am st-b8 st-ao st-ap st-aq st-ar st-as st-at st-au st-av st-aw st-ax st-ay st-az st-b9 st-b1 st-b2 st-b3 st-b4 st-b5 st-b6">
-#         <div class="st-b7">
-#         <div class="css-whx05o e13vu3m50">
-#         <div data-testid="stMarkdownContainer" class="css-1ekf893 e16nr0p30">
-#                 <img src="https://raw.githubusercontent.com/borisdayma/dalle-mini/main/app/streamlit/img/loading.gif" width="30"/>
-#                 Generating predictions for: <b>{prompt}</b>
-#         </div>
-#         </div>
-#         </div>
-#         </div>
-#         </div>
-#         </div>
-#         <small><i>Predictions may take up to 40s under high load. Please stand by.</i></small>
-#     """,
-#         unsafe_allow_html=True,
-#     )
-
-#     print(f"Getting selections: {prompt}")
-#     selected = sample(prompt)
-
-#     margin = 0.1  # for better position of zoom in arrow
-#     n_columns = 3
-#     cols = st.columns([1] + [margin, 1] * (n_columns - 1))
-#     for i, img in enumerate(selected):
-#         cols[(i % n_columns) * 2].image(img)
-#     container.markdown(f"**{prompt}**")
-
-#     st.button("Again!", key="again_button")