update

app.py

@@ -6,6 +6,7 @@ import httpx
 import io
 from PIL import Image
 import PIL
+from functools import lru_cache
 from toolz import pluck
 from piffle.image import IIIFImageClient
 
@@ -33,10 +34,14 @@ def get_image_urls_from_manifest(data):
     return image_urls
 
 
-def resize_iiif_urls(im_url, size='224'):
-    parts = im_url.split("/")
-    parts[6] = f"{size}, {size}"
-    return "/".join(parts)
+def resize_iiif_urls(image_url, size='224'):
+    # parts = im_url.split("/")
+    # parts[6] = f"{size}, {size}"
+    # return "/".join(parts)
+    image_url = IIIFImageClient.init_from_url(image_url)
+    image_url = image_url.size(width=size,height=size)
+    return image_url.__str__()
+
 
 
 async def get_image(client, url):
@@ -52,11 +57,7 @@ async def get_images(urls):
         tasks = [asyncio.ensure_future(get_image(client, url)) for url in urls]
         images = await asyncio.gather(*tasks)
         assert len(images) == len(urls)
-        image_url_tuples = []
-        for url, image in zip(urls, images):
-            if image is not None:
-                image_url_tuples.append((url, image))
-        return image_url_tuples
+        return [(url, image) for url, image in zip(urls, images) if image is not None]
         # return [image for image in images if image is not None]
 
 
@@ -73,10 +74,13 @@ def predict(inputs):
         top_pred = pred[0]
         if top_pred['label'] == 'illustrated':
             image_url = IIIFImageClient.init_from_url(url)
-            image_url = image_url.canonicalize()
-            predicted_images.append((image_url.__str__(), f"Confidence: {top_pred['score']}, page: {10}"))
+            image_url = image_url.size(width=500)
+            image_url = image_url.size(width=500, height='')
+            predicted_images.append((str(image_url), f"Confidence: {top_pred['score']}, \n image url: {image_url}"))
+
     return predicted_images
     # for image in images:
+
     #     top_pred = classif_pipeline(image, top_k=1)[0]
     #     if top_pred['label'] == 'illustrated':
     #         predicted_images.append((image, top_pred['score']))
@@ -87,7 +91,7 @@ gallery.style(grid=3)
 
 demo = gr.Interface(
     fn=predict,
-    inputs=gr.Text(),
+    inputs=gr.Text(label="IIIF manifest url"),
     outputs=gallery,
     title="ImageIN",
     description="Identify illustrations in pages of historical books!",