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@periakiva
periakiva committed Apr 10, 2024
1 parent 31a51fc commit c89775a
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Showing 3 changed files with 1 addition and 35 deletions.
21 changes: 0 additions & 21 deletions angel_system/activity_classification/tcn_hpl/predict.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,9 +156,6 @@ def objects_to_feats(

window_size = len(frame_object_detections)

# print(f"frame_object_detections: {frame_object_detections}")
# print(f"frame_patient_poses: {frame_patient_poses}")
# print(f"frame_patient_poses: {len(frame_patient_poses)}")
# Shape [window_size, None|n_feats]
feature_list: List[Optional[npt.NDArray]] = [None] * window_size
feature_ndim = None
Expand All @@ -171,7 +168,6 @@ def objects_to_feats(
joint_object_offset_all_frames = [None] * window_size
# for pose in frame_patient_poses:
for i, (pose, detection) in enumerate(zip(frame_patient_poses, frame_object_detections)):
# print(f"detection: {detection}")
if detection is None:
continue
labels = detection.labels
Expand All @@ -185,7 +181,6 @@ def objects_to_feats(
# iterate over all detections in that frame
joint_object_offset = []
for j, label in enumerate(labels):
# print(f"label: {label}")
if label == "hand (right)" or label == "hand (left)":
x, y, w, h = bx[j], by[j], bw[j], bh[j]

Expand All @@ -194,11 +189,8 @@ def objects_to_feats(

offset_vector = []
if pose is not None:
# print(f"pose: {pose}")
for joint in pose:
# print(f"joint: {joint}")
jx, jy = joint.positions.x, joint.positions.y
# jx, jy = joint['xy']
joint_point = np.array((jx, jy))
dist = np.linalg.norm(joint_point - hand_point)
offset_vector.append(dist)
Expand All @@ -211,20 +203,14 @@ def objects_to_feats(
joint_right_hand_offset_all_frames[i] = offset_vector
else:
# if objects_joints and num_objects > 0:
# bx, by, bw, bh = xs[i], ys[i], ws[i], hs[i]
# ocx, ocy = bx+(bw//2), by+(bh//2)
x, y, w, h = bx[j], by[j], bw[j], bh[j]
cx, cy = x+(w//2), y+(h//2)
object_point = np.array((cx, cy))
offset_vector = []
if pose is not None:
# print(f"pose: {pose}")
for joint in pose:
# print(f"joint: {joint}")
jx, jy = joint.positions.x, joint.positions.y
# jx, jy = joint['xy']
joint_point = np.array((jx, jy))
# print(f"joint_points: {joint_point.dtype}, object_point: {object_point.dtype}")
dist = np.linalg.norm(joint_point - object_point)
offset_vector.append(dist)
else:
Expand All @@ -233,7 +219,6 @@ def objects_to_feats(

joint_object_offset_all_frames[i] = joint_object_offset

# print(f"det_label_to_idx: {det_label_to_idx}")

for i, frame_dets in enumerate(frame_object_detections):
frame_dets: ObjectDetectionsLTRB
Expand Down Expand Up @@ -270,7 +255,6 @@ def objects_to_feats(
)

offset_vector = []
# if hands_joints:

if joint_left_hand_offset_all_frames[i] is not None:
offset_vector.extend(joint_left_hand_offset_all_frames[i])
Expand All @@ -291,11 +275,6 @@ def objects_to_feats(
else:
offset_vector.extend(zero_offset)

# print(f"num of dets: {len(frame_dets.labels)}")
# print(f"feat length: {len(feat)}")
# print(f"offset_vector length: {len(offset_vector)}")
# print(f"offset_vector: {offset_vector}")

feat.extend(offset_vector)
feat = np.array(feat, dtype=np.float64).ravel()
feat_memo[f_id] = feat
Expand Down
8 changes: 1 addition & 7 deletions angel_system/activity_classification/train_activity_classifier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,9 +39,7 @@ def data_loader(
- ann_by_image: Image id to annotation dict
"""
print("Loading data....")
# Description to ID map.
# print(f"act labels: {act_labels}")
# exit()

act_map = {}
inv_act_map = {}
for step in act_labels["labels"]:
Expand Down Expand Up @@ -316,7 +314,6 @@ def compute_feats(
for joint in pose_keypoints:
jx, jy = joint['xy']
joint_point = np.array((jx, jy))
# print(f"joint_points: {joint_point.dtype}, object_point: {object_point.dtype}")
dist = np.linalg.norm(joint_point - object_point)
offset_vector.append(dist)
else:
Expand Down Expand Up @@ -363,9 +360,6 @@ def compute_feats(
offset_vector.extend(joint_object_offset[i])
else:
offset_vector.extend(zero_offset)

# print(f"feat length: {len(feature_vec)}")
# print(f"offset_vector length: {len(offset_vector)}")

feature_vec.extend(offset_vector)

Expand Down
7 changes: 0 additions & 7 deletions angel_system/activity_classification/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -250,8 +250,6 @@ def obj_det2d_set_to_feature_by_method(
remove_classes_count = [1 for label in non_objects_labels if label in label_to_ind.keys()]
num_det_classes = len(label_to_ind) - len(remove_classes_count)# accomedate 2 hands instead of 1, accomedate top 3 objects

# print(f"label_to_ind: {label_to_ind}")
# print(f"num_det_classes: {num_det_classes}")

det_class_max_conf = np.zeros((num_det_classes, top_n_objects))
# The bounding box of the maximally confident detection
Expand Down Expand Up @@ -284,9 +282,7 @@ def obj_det2d_set_to_feature_by_method(
# util functions
#########################
def find_hand(hand_str):
# hand_str = "hands"
hand_idx = label_to_ind[hand_str]
# print(f"hand_index: {hand_idx}")
hand_conf = det_class_max_conf[hand_idx][0]
hand_bbox = kwimage.Boxes([det_class_bbox[0, hand_idx]], "xywh")

Expand Down Expand Up @@ -461,12 +457,9 @@ def dist_to_center(center1, center2):
if use_hand_dist:
feature_vec.append(right_hand_dist[left_hand_idx])

# print(f"use_hand_dist feature_vec: {len(feature_vec)}")

if use_intersection:
feature_vec.append([right_hand_intersection[left_hand_idx]])

# print(f"use_hand_dist feature_vec: {len(feature_vec)}")
# Add object data
for i in range(num_det_classes):
if i in [right_hand_idx, left_hand_idx]:
Expand Down

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