Clean imports

app.py

@@ -1,22 +1,16 @@
-import streamlit as st
+import io
 import os
+import requests
+import zipfile
+import natsort
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
-import torch
 from pathlib import Path
+import streamlit as st
+from jax import numpy as jnp
 import transformers
 from transformers import AutoTokenizer
-from jax import numpy as jnp
-import json
-import requests
-import zipfile
-import io
-import natsort
-from PIL import Image as PilImage
-
-from torchvision import datasets, transforms
-from torchvision.transforms import CenterCrop, Normalize, Resize, ToTensor
+from torchvision.transforms import Compose, CenterCrop, Normalize, Resize, ToTensor
 from torchvision.transforms.functional import InterpolationMode
-from tqdm import tqdm
 from modeling_hybrid_clip import FlaxHybridCLIP
 
 import utils
@@ -58,12 +52,12 @@ def get_image_features():
 
 # 👋 Ciao!
 
-# CLIP Italian Demo (HF-Flax Community Week)
+# CLIP Italian Demo 
+## HF-Flax Community Week
 """
 
 query = st.text_input("Insert an italian query text here...")
 if query:
-
     with st.spinner("Computing in progress..."):
         model = get_model()
         download_images()
@@ -75,7 +69,7 @@ if query:
 
         image_size = model.config.vision_config.image_size
 
-        val_preprocess = transforms.Compose(
+        val_preprocess = Compose(
             [
                 Resize([image_size], interpolation=InterpolationMode.BICUBIC),
                 CenterCrop(image_size),