Update Dockerfile to optimize application setup and streamline dependencies

main.py

@@ -10,6 +10,7 @@ from typing import Dict, List, Optional
 import cv2
 import numpy as np
 from PIL import Image
+from pillow_lut import load_cube_file
 from fastapi import FastAPI, HTTPException, UploadFile, File
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
@@ -236,39 +237,14 @@ def generate_new_cube(user_prompt: str) -> dict:
 
 
 def apply_lut_to_image(image_path: str, lut_path: str) -> np.ndarray:
-    """Apply LUT to image using OpenCV"""
+    """Apply LUT to image using pillow_lut"""
     try:
-        img = cv2.imread(image_path)
-        if img is None:
-            raise ValueError(f"Could not load image: {image_path}")
-
-        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-
-        transformer = LUTTransformer()
-        if not transformer.parse_cube_file(lut_path):
-            raise ValueError(f"Could not parse LUT file: {lut_path}")
-
-        lut_data = np.array(transformer.lut_data)
-        lut_size = transformer.size
-
-        lut_3d = lut_data.reshape((lut_size, lut_size, lut_size, 3))
-
-        img_normalized = img.astype(np.float32) / 255.0
-
-        result = np.zeros_like(img_normalized)
-
-        for i in range(img.shape[0]):
-            for j in range(img.shape[1]):
-                r, g, b = img_normalized[i, j]
-
-                r_idx = min(int(r * (lut_size - 1)), lut_size - 1)
-                g_idx = min(int(g * (lut_size - 1)), lut_size - 1)
-                b_idx = min(int(b * (lut_size - 1)), lut_size - 1)
-
-                result[i, j] = lut_3d[r_idx, g_idx, b_idx]
-
-        result = np.clip(result * 255, 0, 255).astype(np.uint8)
-        return result
+        lut = load_cube_file(lut_path)
+        im = Image.open(image_path)
+        result_image = im.filter(lut)
+        
+        result_array = np.array(result_image)
+        return result_array
 
     except Exception as e:
         print(f"Error applying LUT to image: {e}")

requirements.txt

@@ -24,6 +24,7 @@ opencv-python==4.12.0.88
 orjson==3.11.0
 packaging==25.0
 pillow==11.3.0
+pillow-lut==1.0.1
 pydantic==2.11.7
 pydantic_core==2.33.2
 python-dotenv==1.1.1