added write to RAM if available

README.md

@@ -49,12 +49,9 @@ poetry build
 poetry publish
 ```
 
-## Todo
--- Preload copaint logo ()
-```
-Loaded image of shape torch.Size([1, 4, 1848, 1844]), from copaint/static/logo_copaint.png
-Image to tensor conversion took 0.0459 seconds
-```
--- Same for insta logo
+## Time bottleneck
+-- the biggest time bottleneck is writing to disk the back image and loading for the PDF creation.
+
 
 
+# Deploy to huggingface.

copaint/copaint.py

@@ -209,6 +209,10 @@ def save_tensor_to_pdf(tensor, pdf_path, is_front=True, margin=0.25, img_small_s
     t3 = time.time()
     # Use PNG for high-res mode instead of JPG
     image_path = "temp.png" if high_res else "temp.jpg"
+    ram_folder_linux = "/dev/shm/"
+    if os.path.exists(ram_folder_linux):
+        image_path = os.path.join(ram_folder_linux, image_path)
+        
     image.save(image_path)
     if debug:
         logger.debug(f"Temporary image saving took {time.time() - t3:.4f} seconds")

copaint/gradio_ui.py

@@ -4,7 +4,7 @@ import gradio as gr
 import shutil
 import tempfile
 import logging
-
+import os
 from gradio_pdf import PDF
 from importlib.resources import files
 from pathlib import Path
@@ -112,8 +112,13 @@ def process_copaint(
 ):
     """Process the input and generate CopainT PDF"""
     # Create temporary directories for processing
-    temp_input_dir = tempfile.mkdtemp()
-    temp_output_dir = tempfile.mkdtemp()
+    # Use /dev/shm if available for better performance
+    if os.path.exists('/dev/shm'):
+        temp_input_dir = tempfile.mkdtemp(dir='/dev/shm')
+        temp_output_dir = tempfile.mkdtemp(dir='/dev/shm')
+    else:
+        temp_input_dir = tempfile.mkdtemp()
+        temp_output_dir = tempfile.mkdtemp()
     
     try:
         # Save uploaded images to temp directory