uninstall old version gradio

app.py

@@ -2,6 +2,7 @@ import os
 import gradio as gr
 print(f"Gradio version {gr.__version__}")
 if gr.__version__ != '4.28.2':
+    os.system("pip uninstall gradio")
     os.system("pip install gradio==4.28.2")
     print(f"Gradio version: {gr.__version__}")
 
@@ -10,9 +11,7 @@ import io
 import torch
 import json
 import base64
-import random
 import numpy as np
-import pandas as pd
 from pathlib import Path
 from PIL import Image
 
@@ -31,24 +30,8 @@ IMAGE2GT = json.load(open("data/jsons/image2gt.json", 'r'))
 CUB_DESC_EMBEDS = torch.load('data/text_embeddings/cub_200_desc.pt').to(DEVICE)
 CUB_IDX2NAME = json.load(open('data/jsons/cub_desc_idx2name.json', 'r'))
 CUB_IDX2NAME = {int(k): v for k, v in CUB_IDX2NAME.items()}
-# correct_predictions = [k for k, v in XCLIP_RESULTS.items() if v['prediction']]
-
-# get the intersection of sachit and xclip (revised)
-# INTERSECTION = []
-# IMAGE_RES = 400 * 400 # minimum resolution
-# TOTAL_SAMPLES = 20
-# for file_name in XCLIP_RESULTS:
-#     image = Image.open(os.path.join(IMAGES_FOLDER, 'org', file_name)).convert('RGB')
-#     w, h = image.size
-#     if w * h < IMAGE_RES:
-#         continue
-#     else:
-#         INTERSECTION.append(file_name)
-
-# IMAGE_FILE_LIST = random.sample(INTERSECTION, TOTAL_SAMPLES)
+
 IMAGE_FILE_LIST = json.load(open("data/jsons/file_list.json", "r"))
-# IMAGE_FILE_LIST = IMAGE_FILE_LIST[:19]
-# IMAGE_FILE_LIST.append('Eastern_Bluebird.jpg')
 IMAGE_GALLERY = [Image.open(os.path.join(IMAGES_FOLDER, 'org', file_name)).convert('RGB') for file_name in IMAGE_FILE_LIST]
 
 ORG_PART_ORDER = ['back', 'beak', 'belly', 'breast', 'crown', 'forehead', 'eyes', 'legs', 'wings', 'nape', 'tail', 'throat']