- tweaks

README.md

@@ -1,5 +1,5 @@
 ---
-title: FindYourSiblings
+title: FindYourTwins
 emoji: 📉
 colorFrom: green
 colorTo: red

app.py

@@ -16,7 +16,7 @@ with gr.Blocks() as demo:
         """
         # Find Your Twins
 
-        Upload your face and find the most similar people from [Face Aging Dataset](https://huggingface.co/datasets/BounharAbdelaziz/Face-Aging-Dataset) using Google's [VIT](https://huggingface.co/google/vit-base-patch16-224-in21k) model. The task of finding most similar vectors is powered by [Upstash Vector](https://upstash.com) 🚀. Check our blog post *here*.
+        Upload your face and find the most similar faces from [Face Aging Dataset](https://huggingface.co/datasets/BounharAbdelaziz/Face-Aging-Dataset) using Google's [VIT](https://huggingface.co/google/vit-base-patch16-224-in21k) model. For best results please use 1x1 ratio face images, take a look at examples. The Vector similarity search is powered by [Upstash Vector](https://upstash.com) 🚀. You can check our blog *post* to learn more.
         """
     )
 
@@ -25,10 +25,9 @@ with gr.Blocks() as demo:
             with gr.Column(scale=1):
                 input_image = gr.Image(type="pil")
             with gr.Column(scale=2):
-                output_image = gr.Gallery(height=450)
+                output_images = gr.Gallery()
 
-
-        @input_image.change(inputs=input_image, outputs=output_image)
+        @input_image.change(inputs=input_image, outputs=output_images)
         async def find_similar_faces(image):
             if image is None:
                 return None
@@ -38,11 +37,14 @@ with gr.Blocks() as demo:
             result = await index.query(vector=embed.tolist(), top_k=4)
             return [dataset["train"][int(vector.id)]["image"] for vector in result]
 
-
         gr.Examples(
-            examples=[dataset["train"][6]["image"], dataset["train"][7]["image"], dataset["train"][8]["image"]],
+            examples=[
+                dataset["train"][6]["image"],
+                dataset["train"][7]["image"],
+                dataset["train"][8]["image"],
+            ],
             inputs=input_image,
-            outputs=output_image,
+            outputs=output_images,
             fn=find_similar_faces,
             cache_examples=False,
         )
@@ -51,26 +53,31 @@ with gr.Blocks() as demo:
         with gr.Row():
             with gr.Column(scale=1):
                 adv_input_image = gr.Image(type="pil")
-                adv_image_count = gr.Number(9, label="Image Count")
+                adv_image_count = gr.Slider(1, 30, 10, label="Image Count")
                 adv_button = gr.Button("Submit")
 
             with gr.Column(scale=2):
                 adv_output_image = gr.Gallery()
 
-
-        @adv_button.click(inputs=[adv_input_image, adv_image_count], outputs=[adv_output_image])
         async def find_similar_faces(image, count):
             inputs = extractor(images=image, return_tensors="pt")
             outputs = model(**inputs)
             embed = outputs.last_hidden_state[0][0]
             result = await index.query(
-                vector=embed.tolist(), top_k=max(1, min(19, count))
+                vector=embed.tolist(), top_k=max(1, min(30, count))
             )
             return [dataset["train"][int(vector.id)]["image"] for vector in result]
 
-
-        adv_input_image.upload(fn=find_similar_faces, inputs=[adv_input_image, adv_image_count],
-                               outputs=[adv_output_image])
+        adv_button.click(
+            fn=find_similar_faces,
+            inputs=[adv_input_image, adv_image_count],
+            outputs=[adv_output_image],
+        )
+        adv_input_image.upload(
+            fn=find_similar_faces,
+            inputs=[adv_input_image, adv_image_count],
+            outputs=[adv_output_image],
+        )
 
 if __name__ == "__main__":
     demo.launch(debug=True, share=True)