huge changes

filmscan

@@ -314,8 +314,8 @@ def negadoctor_process(img_aces_negative: np.ndarray,
         
         compressed_highlights = soft_clip_param + (1.0 - e_to_gamma) * soft_clip_comp
         output_pixels = np.where(print_gamma > soft_clip_param, compressed_highlights, print_gamma)
-        
-    return np.clip(output_pixels, 0.0, 1.0) # Final clip to 0-1 range
+
+    return np.clip(output_pixels, 0.0, None) # Final clip to 0-Inf range
 
 
 # --- Main Execution ---
@@ -371,10 +371,26 @@ if __name__ == "__main__":
     print("Converting to ACEScg...")
     # img_linear_srgb = colour.gamma_correct(img_float, 1/2.2, 'ITU-R BT.709') # Approximate sRGB EOTF decoding
     img_linear_srgb = colour.models.eotf_sRGB(img_float) # More accurate sRGB EOTF decoding
-    img_acescg = colour.RGB_to_RGB(img_linear_srgb,
-                                   colour.models.RGB_COLOURSPACE_sRGB,
-                                   colour.models.RGB_COLOURSPACE_ACESCG)
-    img_acescg = np.clip(img_acescg, 0.0, None) # ACEScg can have values > 1.0 for very bright sources
+    # Calculate the full transformation matrix from linear sRGB to ACEScg.
+    # This includes chromatic adaptation from sRGB's D65 whitepoint 
+    # to ACEScg's D60 whitepoint, which is crucial for accuracy.
+    sRGB_cs = colour.models.RGB_COLOURSPACE_sRGB
+    ACEScg_cs = colour.models.RGB_COLOURSPACE_ACESCG
+    
+    # colour.matrix_RGB_to_RGB computes the combined matrix: M_XYZ_to_ACEScg @ M_CAT @ M_sRGB_to_XYZ
+    # This matrix is cached by colour-science after the first call for efficiency.
+    srgb_to_acescg_matrix = colour.matrix_RGB_to_RGB(sRGB_cs, ACEScg_cs) # Shape: (3, 3)
+
+    # Apply the transformation using NumPy's matrix multiplication operator @.
+    # img_linear_srgb has shape (H, W, 3).
+    # srgb_to_acescg_matrix.T also has shape (3, 3).
+    # The @ operator performs (H, W, 3) @ (3, 3) -> (H, W, 3),
+    # effectively applying the 3x3 matrix to each 3-element RGB vector.
+    # This is generally highly optimized and avoids explicit reshape calls.
+    img_acescg = img_linear_srgb @ srgb_to_acescg_matrix.T
+    
+    # ACEScg space can legitimately have values outside [0,1] for bright, saturated colors.
+    img_acescg = np.clip(img_acescg, 0.0, None) 
 
     print(f"Image in ACEScg: shape: {img_acescg.shape}, min: {img_acescg.min():.4f}, max: {img_acescg.max():.4f}, mean: {img_acescg.mean():.4f}")