Update app.py

app.py

@@ -17,36 +17,8 @@ caption_image = pipeline("image-to-text", model="Salesforce/blip-image-captionin
 # Load the text-to-speech pipeline
 narrator = pipeline("text-to-speech", model="kakao-enterprise/vits-ljs", device=device)
 
-
-# URLs of the images
-image_urls = [
-    "https://github.com/Walid-Ahmed/ML_Datasets/blob/master/image1.jpeg?raw=true",
-    "https://github.com/Walid-Ahmed/ML_Datasets/blob/master/image2.jpeg?raw=true",
-    "https://github.com/Walid-Ahmed/ML_Datasets/blob/master/image3.jpeg?raw=true"
-]
-
-# Directory to save images
-save_dir = "example_images"
-os.makedirs(save_dir, exist_ok=True)
-
-# Function to download images
-def download_image(url, filename):
-    response = requests.get(url)
-    if response.status_code == 200:
-        with open(filename, "wb") as f:
-            f.write(response.content)
-        return filename
-    else:
-        print(f"Failed to download: {url}")
-        return None
-
-# Download images
-example_images = []
-for idx, url in enumerate(image_urls):
-    img_path = os.path.join(save_dir, f"image{idx+1}.jpeg")
-    if not os.path.exists(img_path):  # Avoid redownloading if already exists
-        download_image(url, img_path)
-    example_images.append(img_path)
+# List of local image paths
+example_images = ["image1.jpeg", "image2.jpeg", "image3.jpeg"]
 
 def process_image(image):
     # Generate the caption