improved latency: passing urls to gallery directly

app.py

@@ -21,7 +21,7 @@ embeddings = torch.tensor(embeddings)
 
 img_df = pd.read_csv('image_data.csv')
 
-def url2img(url, resize = False, fix_height = 200):
+def url2img(url, resize = False, fix_height = 150):
     data = requests.get(url, allow_redirects = True).content
     img = Image.open(io.BytesIO(data))
     if resize:
@@ -32,7 +32,7 @@ def find_topk(text):
 
     print('text', text)
 
-    top_k = 10
+    top_k = 20
 
     text_data = model_multi.preprocess_text(text)
     text_features, text_embedding = model_multi.encode_text(text_data, return_features=True)
@@ -44,15 +44,10 @@ def find_topk(text):
     vals, inds = sims.topk(top_k)
     top_k_urls = img_df.iloc[inds]['photo_image_url'].values
 
-    print('top_k_urls', top_k_urls)
+    print('Got top_k_urls', top_k_urls)
     print(datetime.now().strftime("%H:%M:%S"))
 
-    images = [url2img(url, resize = False) for url in top_k_urls]
-
-    print('got PIL images')
-    print(datetime.now().strftime("%H:%M:%S"))
-
-    return images
+    return top_k_urls
 
 
 
@@ -91,7 +86,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                 prompt_box = gr.Textbox(label = 'Enter your prompt', lines = 3)
                 btn_search = gr.Button("Find images")
 
-        gallery = gr.Gallery().style(columns=5, rows=2, object_fit="contain", height="auto")
+        gallery = gr.Gallery().style(columns = [5],  height="auto", object_fit = "scale-down")
         btn_search.click(find_topk, inputs = prompt_box, outputs = gallery)
 
 if __name__ == "__main__":