Update app.py

app.py

@@ -12,6 +12,7 @@ import os
 from dotenv import load_dotenv
 import base64
 import io
+import concurrent.futures
 
 # Load environment variables from .env file
 load_dotenv()
@@ -40,6 +41,9 @@ def generate_captions_from_image(image):
     if image.mode != "RGB":
         image = image.convert("RGB")
     
+    # Resize image for faster processing
+    image = image.resize((640, 640))
+    
     # Preprocess the image and generate a caption
     inputs = processor(image, return_tensors="pt").to(device, torch.float16)
     output = model.generate(**inputs, max_new_tokens=50)
@@ -136,16 +140,12 @@ def generate_dpr(files):
     # Add header to the DPR
     dpr_text.append(f"Daily Progress Report\nGenerated on: {current_time}\n")
     
-    # Process each uploaded file (image)
-    for file in files:
-        # Open the image from file path
-        image = Image.open(file.name)
-        
-        if image.mode != "RGB":
-            image = image.convert("RGB")
-        
-        # Dynamically generate a caption based on the image
-        caption = generate_captions_from_image(image)
+    # Process images in parallel for faster performance
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        results = list(executor.map(lambda file: generate_captions_from_image(Image.open(file.name)), files))
+    
+    for i, file in enumerate(files):
+        caption = results[i]
         captions.append(caption)
         
         # Generate DPR section for this image with dynamic caption