Update app.py

app.py

@@ -12,7 +12,7 @@ processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
 # Load the Unsplash dataset
 dataset = load_dataset("jamescalam/unsplash-25k-photos", split="train")  # all 25K images are in train split
 
-height = 250   # height for resizing images
+height = 256   # height for resizing images
 
 def predict(image, labels):
     inputs = processor(text=[f"a photo of {c}" for c in labels], images=image, return_tensors="pt", padding=True)
@@ -24,7 +24,7 @@ def predict(image, labels):
 def rand_image():
     n = dataset.num_rows
     r = random.randrange(0,n)
-    return dataset[r]["photo_image_url"] # + f"?h={height}"  # Unsplash allows dynamic requests, including size of image
+    return dataset[r]["photo_image_url"] + f"?h={height}"  # Unsplash allows dynamic requests, including size of image
 
 def set_labels(text):
     return text.split(",")