EKF-Diagnostic/sensor-anomalies
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additions from Susanne #14

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foefl merged 2 commits from new_main into main 2025-11-10 07:40:15 +00:00
Conversation 0 Commits 2 Files Changed 1 +5 -5
1 changed files with 5 additions and 5 deletions
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10
src/dopt_sensor_anomalies/detection.py
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@ -140,10 +140,10 @@ def measure_length(
f"expected value: count = {num_contours}, expected = {const.NUM_VALID_ELECTRODES}" f"expected value: count = {num_contours}, expected = {const.NUM_VALID_ELECTRODES}"
) )
x_min = min(np.min(c[:, 0, 0]) for c in filtered_cnts) - 20 x_min = max(min(np.min(c[:, 0, 0]) for c in filtered_cnts) - 20, 0)
x_max = max(np.max(c[:, 0, 0]) for c in filtered_cnts) + 20 x_max = min(max(np.max(c[:, 0, 0]) for c in filtered_cnts) + 20, orig.shape[1])
y_min = min(np.min(c[:, 0, 1]) for c in filtered_cnts) - 20 y_min = max(min(np.min(c[:, 0, 1]) for c in filtered_cnts) - 20, 0)
y_max = max(np.max(c[:, 0, 1]) for c in filtered_cnts) + 20 y_max = min(max(np.max(c[:, 0, 1]) for c in filtered_cnts) + 20, orig.shape[0])
rightmost_x_third = max(filtered_cnts[2][:, 0, 0]) rightmost_x_third = max(filtered_cnts[2][:, 0, 0])
leftmost_x_fourth = min(filtered_cnts[3][:, 0, 0]) leftmost_x_fourth = min(filtered_cnts[3][:, 0, 0])
@ -176,7 +176,7 @@ def infer_image(
output = model(input_tensor) output = model(input_tensor)
anomaly_score = output.pred_score.item() anomaly_score = output.pred_score.item()
anomaly_label = output.pred_label.item() anomaly_label = 1 if anomaly_score >= .2 else 0
anomaly_map = output.anomaly_map.squeeze().cpu().numpy() anomaly_map = output.anomaly_map.squeeze().cpu().numpy()
img_np = np.array(pil_image) img_np = np.array(pil_image)