add animation

.gitattributes

@@ -14,3 +14,7 @@
 *.pb filter=lfs diff=lfs merge=lfs -text
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text
+gif/EV0ucJyWkAAXPKx.gif filter=lfs diff=lfs merge=lfs -text
+gif/EV1WRb_WoAAFXGj.gif filter=lfs diff=lfs merge=lfs -text
+gif/EVvxHs8XgAA3lhG.gif filter=lfs diff=lfs merge=lfs -text
+gif/EVx4DsWWkAADKOk.gif filter=lfs diff=lfs merge=lfs -text

app.py

@@ -34,7 +34,7 @@ with st.sidebar.beta_expander("Motivation",expanded=True):
     )
 top_k=st.sidebar.slider("Show top-K", min_value=1, max_value=50, value=20)
 col_count=4
-file_names=os.listdir("./imgs")
+file_names=os.listdir("./jpg")
 file_names.sort()
 
 show_val=st.sidebar.button("show all validation set images")
@@ -42,7 +42,7 @@ if show_val:
     cols=st.sidebar.beta_columns(col_count)
     for i,im in enumerate(file_names):
         j=i%col_count
-        cols[j].image("./imgs/"+im)
+        cols[j].image("./jpg/"+im)
 
 st.write("# Search Reaction GIFs with CLIP")
 st.write("    ")
@@ -82,7 +82,13 @@ def add_image_emb(image):
 
 
 def query_with_images(query_images,query_text):
-    images = [Image.open(im).convert("RGB") for im in query_images]
+    images=[]
+    for im in query_images: 
+        img=Image.open(im).convert("RGB")
+        if im.name.endswith(".gif"):
+            img.seek(0)
+        images.append(img)
+
     inputs = processor(text=[query_text], images=images, return_tensors="jax", padding=True)
     inputs["pixel_values"] = jnp.transpose(inputs["pixel_values"], axes=[0, 2, 3, 1])
     outputs = model(**inputs)
@@ -109,7 +115,7 @@ q_cols[2].markdown(
 )
 
 query_text = q_cols[0].text_input("Write text you want to get reaction for", value=example_input)
-query_images = q_cols[2].file_uploader("(optional) Upload images to rank them",type=['jpg','jpeg'], accept_multiple_files=True)
+query_images = q_cols[2].file_uploader("(optional) Upload images to rank them",type=['jpg','jpeg','gif'], accept_multiple_files=True)
 
 if query_images:
     st.write("Ranking your uploaded images with respect to input text:")
@@ -120,12 +126,14 @@ else:
     vec = np.asarray(model.get_text_features(**proc))
     ids, dists = image_index.knnQuery(vec, k=top_k)
 
+show_gif=st.checkbox("Play GIFs",value=True,help="Will play the original animation. Only first frame is used in training!")
+ext = "jpg" if not show_gif else "gif"
 res_cols=st.beta_columns(col_count)
 for i,(id_, dist) in enumerate(zip(ids, dists)):
     j=i%col_count
     with res_cols[j]:
         if isinstance(id_, np.int32):
-            st.image("./imgs/"+file_names[id_])
+            st.image(f"./{ext}/{file_names[id_][:-4]}.{ext}")
             # st.write(file_names[id_])
             st.write(1.0 - dist, help="score")
         else: