different thresholds for noise detection methods

mio/data/config/process/denoise_example_mean_error.yml

@@ -0,0 +1,35 @@
+id: denoise_example_mean_error
+mio_model: mio.models.process.DenoiseConfig
+mio_version: 0.6.1
+interactive_display:
+  enable: true
+  start_frame: 40
+  end_frame: 140
+noise_patch:
+  enable: true
+  method: mean_error
+  threshold: 30
+  buffer_size: 5032
+  buffer_split: 8
+  diff_multiply: 1
+  output_result: true
+  output_noise_patch: true
+  output_diff: true
+  output_noisy_frames: true
+frequency_masking:
+  enable: true
+  spatial_LPF_cutoff_radius: 15
+  vertical_BEF_cutoff: 2
+  horizontal_BEF_cutoff: 0
+  display_mask: false
+  output_mask: true
+  output_result: true
+  output_freq_domain: false
+minimum_projection:
+  enable: true
+  normalize: true
+  output_result: true
+  output_min_proj: true
+end_frame: -1 #-1 means all frames
+output_result: true
+output_dir: user_dir/output

mio/process/frame_helper.py

@@ -90,8 +90,9 @@ def detect_frame_with_noisy_buffer(
             serialized_previous = previous_frame.flatten().astype(np.int16)
             logger.debug(f"Serialized previous frame size: {len(serialized_previous)}")
 
-            split_previous = self.split_by_length(serialized_previous, config.buffer_size)
-            split_current = self.split_by_length(serialized_current, config.buffer_size)
+            split_size = config.buffer_size // config.buffer_split + 1
+            split_previous = self.split_by_length(serialized_previous, split_size)
+            split_current = self.split_by_length(serialized_current, split_size)
 
             return self._detect_with_mean_error(split_current, split_previous, config)
 
@@ -122,7 +123,6 @@ def _detect_with_mean_error(
             f"Actual total splits in current: {len(split_current)}, previous: {len(split_previous)}"
         )
 
-
         # Iterate over buffers and split sections
         logger.debug(
             f"Entering mean_error loop: Total splits: {len(split_current)}, "

tests/test_process/test_frame_helper.py

@@ -8,6 +8,7 @@
 
 from ..conftest import DATA_DIR
 
+
 @pytest.mark.parametrize(
     "noise_detection_method",
     [
@@ -20,7 +21,13 @@ def test_noise_detection_contrast(noise_detection_method):
     Contrast method of noise detection should correctly label frames corrupted
     by speckled noise
     """
-    global_config: DenoiseConfig = DenoiseConfig.from_id("denoise_example")
+    if noise_detection_method == "gradient":
+        global_config: DenoiseConfig = DenoiseConfig.from_id("denoise_example")
+    elif noise_detection_method == "mean_error":
+        global_config: DenoiseConfig = DenoiseConfig.from_id("denoise_example_mean_error")
+    else:
+        raise ValueError("Invalid noise detection method")
+
     config: NoisePatchConfig = global_config.noise_patch
     config.method = noise_detection_method
 
@@ -45,19 +52,17 @@ def test_noise_detection_contrast(noise_detection_method):
         frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
         if noise_detection_method == "gradient":
             is_noisy, mask = detector.detect_frame_with_noisy_buffer(
-                current_frame = frame,
-                previous_frame = None,
-                config = config)
+                current_frame=frame, previous_frame=None, config=config
+            )
         if noise_detection_method == "mean_error":
             if previous_frame is None:
                 previous_frame = frame
             is_noisy, mask = detector.detect_frame_with_noisy_buffer(
-                current_frame = frame,
-                previous_frame = previous_frame,
-                config = config)
+                current_frame=frame, previous_frame=previous_frame, config=config
+            )
             if not is_noisy:
                 previous_frame = frame
         frames.append(is_noisy)
         masks.append(mask)
 
-    assert np.array_equal(np.where(frames)[0], expected["frames"])
+    assert np.array_equal(np.where(frames)[0], expected["frames"])