Ensure GIFs can be visualized as well

app.py

@@ -77,6 +77,8 @@ def init():
     # ja_image_features = np.load("./hakuhodo_features.npy")
     ml_image_features = np.load("./resized_ml_features.npy")
     ja_image_features = np.load("./resized_ja_features.npy")
+    # ml_image_features = np.load("./tiled_ml_features.npy")
+    # ja_image_features = np.load("./tiled_ja_features.npy")
 
     # Convert features to Tensors: Float32 on CPU and Float16 on GPU
     if device == "cpu":
@@ -188,7 +190,7 @@ def visualize_gradcam(viz_image_id):
 
     image_url = st.session_state.images_info.loc[viz_image_id]["image_url"]
     image_response = requests.get(image_url)
-    image = Image.open(BytesIO(image_response.content), formats=["JPEG"])
+    image = Image.open(BytesIO(image_response.content), formats=["JPEG", "GIF"])
 
     img_dim = 224
     if st.session_state.active_model == "M-CLIP (multiple languages)":
@@ -309,7 +311,7 @@ def visualize_gradcam(viz_image_id):
 
             progress_bar.progress(
                 (t + 1) / len(tokenized_text),
-                text=f"Processing token {t+1} of {len(tokenized_text)} tokens",
+                text=f"Processing token {t+1} of {len(tokenized_text)}",
             )
         progress_bar.empty()
 
@@ -381,7 +383,7 @@ with search_row[3]:
 with search_row[4]:
     st.radio(
         "CLIP Model",
-        options=["M-CLIP (multiple languages)", "J-CLIP (日本語 only)"],
+        options=["M-CLIP (multiple languages)", "J-CLIP (日本語)"],
         key="active_model",
         on_change=string_search,
         horizontal=True,