Update app.py

app.py

@@ -7,17 +7,6 @@ from dotenv import load_dotenv
 import google.generativeai as genai
 import os
 
-# from openai import OpenAI
-# client = OpenAI(api_key="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")
-# import base64
-
-# # Open the image file and encode it as a base64 string
-# def encode_image(image_path):
-#     with open(image_path, "rb") as image_file:
-#         return base64.b64encode(image_file.read()).decode("utf-8")
-
-#load_dotenv()
-#GOOGLE_API_KEY = os.getenv("AIzaSyByqW3ByYPxC4xLS_NhgwAOAMMEgB7DvoY")
 genai.configure(api_key="AIzaSyByqW3ByYPxC4xLS_NhgwAOAMMEgB7DvoY")
 model_vision = genai.GenerativeModel('gemini-1.5-flash')
 
@@ -59,7 +48,6 @@ inputs = [
     gr.Textbox(lines=1, 
                       label="Prior Domains", placeholder="Add a domain label, one by one"),
 ]
-images="festival.jpg"
 
 def shot(image, labels_text, model_name, hypothesis_template_prefix, hypothesis_template_suffix, domains_text):
     labels = [label.strip(" ") for label in labels_text.strip(" ").split(",")]
@@ -87,13 +75,12 @@ iface = gr.Interface(shot,
             inputs, 
             "label", 
             examples=[
-                    #["festival.jpg", "lantern, firecracker, couplet", "ViT/B-16", "a photo of a {}", "in {} {} {} from {} with {}.", "clear, autumn, day, side, partial occlusion"],
                      ["car_occlusion.png", "car, bus, truck", "ViT/B-16", "a photo of a {}", "in {} {} {} from {} with {}.", ""],
                     ["foggy_motor.png", "car, bus, truck", "ViT/B-16", "a photo of a {}", "in {} {} {} from {} with {}.", ""],
                     ["night_truck.png", "car, bus, truck", "ViT/B-16", "a photo of a {}", "in {} {} {} from {} with {}.", "clear, autumn, night, side, no occlusion"],
                     ["rainy_front_truck.png", "car, bus, truck", "ViT/B-16", "a photo of a {}", "in {} {} {} from {} with {}.", ""],
                     ["truck_top.png", "car, bus, truck", "ViT/B-16", "a photo of a {}", "in {} {} {} from {} with {}.", "clear, summer, day, top, no occlusion"],], 
-            description="""<p> <br><br>
+            description="""<p> Demo for Domain CLIP, an algorithm for Training-Free Adaptive Domain Generalization. For more information about our project, refer to our paper.<br><br>
             Paper: <a href='https://arxiv.org/pdf/2403.02714'>https://arxiv.org/pdf/2403.02714</a> <br>
             To begin with the demo, provide a picture (either upload manually, or select from the given examples) and add class labels one by one. Optionally, you can also add template as a prefix to the class labels. <br>""",
             title="Cross-Domain Recognition")