update stereogram method

app.py

@@ -6,16 +6,19 @@ import numpy as np
 from PIL import Image, ImageOps
 from pathlib import Path
 import glob
-from autostereogram.sirds_converter import SirdsConverter
+from autostereogram.converter import StereogramConverter
 from datetime import datetime
+import time
 
 feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-large")
 model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
 
-stereo_converter = SirdsConverter()
-
+stereo_converter = StereogramConverter()
 
 def process_image(image_path):
+    print("\n\n\n")
+    print("Processing image:", image_path)
+    last_time = time.time()
     image_raw = Image.open(Path(image_path))
 
     image = image_raw.resize(
@@ -38,16 +41,18 @@ def process_image(image_path):
         align_corners=False,
     ).squeeze()
     output = prediction.cpu().numpy()
-    depth_image = (255 - output * 255 / np.max(output)).astype('uint8')
+    depth_image = (output * 255 / np.max(output)).astype('uint8')
     depth_image_padded = np.array(ImageOps.pad(
         Image.fromarray(depth_image), (1280, 720)))
 
-    stereo_image = stereo_converter.convert_depth_to_stereogram_with_sird(
-        depth_image_padded, False, 0.5).astype(np.uint8)
+    stereo_image = stereo_converter.convert_depth_to_stereogram_with_thread_pool(
+        depth_image_padded, False).astype(np.uint8)
 
     stereo_image_pil = Image.fromarray(stereo_image).convert('RGB')
     image_name = f'stereo_image_{datetime.now().strftime("%Y%m%d_%H%M%S")}.jpg'
     stereo_image_pil.save(image_name)
+    print(time.time() - last_time)
+    print("\n\n\n")
     return [depth_image_padded, stereo_image, image_name]