Add title and examples (#2)

- Add title and examples (8feee7f034346f43f08b80f672ba3fe95f566d8f)

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,3 +1,5 @@
+import pathlib
+
 import gradio as gr
 import open_clip
 import torch
@@ -8,14 +10,23 @@ model, _, transform = open_clip.create_model_and_transforms(
     "coca_ViT-L-14",
     pretrained="mscoco_finetuned_laion2B-s13B-b90k"
 )
-
 model.to(device)
 
+
 def output_generate(image):
     im = transform(image).unsqueeze(0).to(device)
     with torch.no_grad(), torch.cuda.amp.autocast():
         generated = model.generate(im, seq_len=20)
     return open_clip.decode(generated[0].detach()).split("<end_of_text>")[0].replace("<start_of_text>", "")
 
-iface = gr.Interface(fn=output_generate, inputs=gr.Image(type="pil"), outputs="text")
-iface.launch()
+
+paths = sorted(pathlib.Path("images").glob("*.jpg"))
+
+iface = gr.Interface(
+    fn=output_generate,
+    inputs=gr.Image(label="Input image", type="pil"),
+    outputs=gr.Text(label="Caption output"),
+    title="CoCa: Contrastive Captioners are Image-Text Foundation Models",
+    examples=[path.as_posix() for path in paths],
+)
+iface.launch()