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analysing problem

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luni
2023-01-29 19:54:39 +00:00
parent 1c24bc0d0e
commit 5758adc688
1 changed files with 5 additions and 4 deletions
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curvature_analysis.py
+5 -4
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@@ -132,7 +132,7 @@ def generate_curvatures(v, faces, mask, neighbourhood=25, nr_of_labels=6):
frame_labels[(curvature >= bins[j]) * (curvature < bins[j+1])] = labels[j] frame_labels[(curvature >= bins[j]) * (curvature < bins[j+1])] = labels[j]
frame_labels[curvature >= bins[-2]] = labels[-1] frame_labels[curvature >= bins[-2]] = labels[-1]
return frame_labels return frame_labels, curvature
import tensorflow as tf import tensorflow as tf
from configs.config_abl_overfit_jumpsuit_2 import config from configs.config_abl_overfit_jumpsuit_2 import config
@@ -185,14 +185,15 @@ def visualize_curvature_labels(folder, results_folder, frame):
uv_curvature = np.load(os.path.join(folder, 'uv_curvature', f'{id}_{frame_nr}.npz'))['curvature_uv'] uv_curvature = np.load(os.path.join(folder, 'uv_curvature', f'{id}_{frame_nr}.npz'))['curvature_uv']
mesh_curvature = np.load(os.path.join(folder, 'mesh_curvature', f'{id}_{frame_nr}.npz'))['mesh_curvature'][mask] mesh_curvature = np.load(os.path.join(folder, 'mesh_curvature', f'{id}_{frame_nr}.npz'))['mesh_curvature'][mask]
mesh_curvature_raw = np.load(os.path.join(folder, 'mesh_curvature_raw', f'{id}_{frame_nr}.npz'))['mesh_curvature_raw'][mask]
uv_curvature = tf.one_hot(uv_curvature, 7) uv_curvature = tf.one_hot(uv_curvature, 7)
pred_new = get_prediction(folder, frame, uv_curvature) pred_new = get_prediction(folder, frame, uv_curvature)
pred_new = postprocess(pred_new, faces) pred_new = postprocess(pred_new, faces)
curvature_labels_gt = generate_curvatures(verts, faces, mask, 25) curvature_labels_gt, curv_gt = generate_curvatures(verts, faces, mask, 25)
curvature_labels_pred = generate_curvatures(pred, faces, mask, 25) curvature_labels_pred, _ = generate_curvatures(pred, faces, mask, 25)
curvatures_new = (uv2meshlabel(uv_curvature[None,:,:,:])[0].numpy() * mask[:,None])[mask, :] curvatures_new = (uv2meshlabel(uv_curvature[None,:,:,:])[0].numpy() * mask[:,None])[mask, :]
curvatures_pred_new = generate_curvatures(pred_new, faces, mask, 25) curvatures_pred_new, curv_gt_new = generate_curvatures(pred_new, faces, mask, 25)
dice = dice_dense(tf.one_hot(curvature_labels_pred, 7)[None,:], tf.one_hot(curvature_labels_gt, 7)[None,:]) dice = dice_dense(tf.one_hot(curvature_labels_pred, 7)[None,:], tf.one_hot(curvature_labels_gt, 7)[None,:])
dice_new = dice_dense(tf.one_hot(curvatures_pred_new, 7)[None,:], curvatures_new[None,:]) dice_new = dice_dense(tf.one_hot(curvatures_pred_new, 7)[None,:], curvatures_new[None,:])
curvatures_new = curvatures_new.argmax(axis=-1) - 1 curvatures_new = curvatures_new.argmax(axis=-1) - 1