Skip to content

skeleton-based HAR demo bug fixed #260

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 5 commits into from
Jun 7, 2022
Merged

skeleton-based HAR demo bug fixed #260

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
d6d2edb
infer updated
negarhdr Jun 2, 2022
da93dd5
edge case fix (no pose detected)
passalis Jun 4, 2022
00d2f31
pep fixes
passalis Jun 4, 2022
dc181e1
Fix sources after cppcheck upgrade
ad-daniel Jun 7, 2022
5760d67
More
ad-daniel Jun 7, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 5 additions & 4 deletions projects/perception/skeleton_based_action_recognition/demos/demo.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -205,10 +205,11 @@ def draw_preds(frame, preds: Dict):
if counter > 0:
skeleton_seq = pose2numpy(args, counter, poses_list)

prediction = action_classifier.infer(skeleton_seq)
category_labels = preds2label(prediction.confidence)
print(category_labels)
draw_preds(img, category_labels)
prediction = action_classifier.infer(skeleton_seq)
category_labels = preds2label(prediction.confidence)
print(category_labels)
draw_preds(img, category_labels)

# Calculate a running average on FPS
end_time = time.perf_counter()
fps = 1.0 / (end_time - start_time)
Expand Down
24 changes: 12 additions & 12 deletions src/c_api/face_recognition.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -289,20 +289,20 @@ void build_database_face_recognition(const char *database_folder, const char *ou
// Write number of persons
int n = person_names.size();

fout.write((char *)(&n), sizeof(int));
fout.write(static_cast<char *>(&n), sizeof(int));
for (int i = 0; i < n; i++) {
// Write the name of the person (along with its size)
int name_length = person_names[i].size() + 1;
fout.write((char *)(&name_length), sizeof(int));
fout.write(static_cast<char *>(&name_length), sizeof(int));
fout.write(person_names[i].c_str(), name_length);
}

cv::Size s = database_out.size();

fout.write((char *)(&s.height), sizeof(int));
fout.write((char *)(&s.width), sizeof(int));
fout.write((char *)database_out.data, sizeof(float) * s.height * s.width);
fout.write((char *)(&database_ids[0]), sizeof(int) * s.height);
fout.write(static_cast<char *>(&s.height), sizeof(int));
fout.write(static_cast<char *>(&s.width), sizeof(int));
fout.write(static_cast<char *>(database_out.data), sizeof(float) * s.height * s.width);
fout.write(static_cast<char *>(&database_ids[0]), sizeof(int) * s.height);
fout.flush();
fout.close();
}
Expand All @@ -318,14 +318,14 @@ void load_database_face_recognition(const char *database_path, face_recognition_
return;
}
int n;
fin.read((char *)(&n), sizeof(int));
fin.read(static_cast<char *>(&n), sizeof(int));
char **person_names = new char *[n];

for (int i = 0; i < n; i++) {
person_names[i] = new char[512];
// Read person name
int name_length;
fin.read((char *)(&name_length), sizeof(int));
fin.read(static_cast<char *>(&name_length), sizeof(int));
if (name_length > 512) {
std::cerr << "Person name exceeds max number of characters (512)" << std::endl;
return;
Expand All @@ -334,13 +334,13 @@ void load_database_face_recognition(const char *database_path, face_recognition_
}

int height, width;
fin.read((char *)(&height), sizeof(int));
fin.read((char *)(&width), sizeof(int));
fin.read(static_cast<char *>(&height), sizeof(int));
fin.read(static_cast<char *>(&width), sizeof(int));

float *database_buff = new float[height * width];
int *features_ids = new int[height];
fin.read((char *)(database_buff), sizeof(float) * height * width);
fin.read((char *)(features_ids), sizeof(int) * height);
fin.read(static_cast<char *>(database_buff), sizeof(float) * height * width);
fin.read(static_cast<char *>(features_ids), sizeof(int) * height);

fin.close();

Expand Down
3 changes: 1 addition & 2 deletions ...r/perception/skeleton_based_action_recognition/progressive_spatio_temporal_gcn_learner.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -566,10 +566,9 @@ def infer(self, skeletonseq_batch):

m = nn.Softmax(dim=0)
softmax_predictions = m(output.data[0])
class_confidence = float(torch.max(softmax_predictions))
class_ind = int(torch.argmax(softmax_predictions))
class_description = self.classes_dict[class_ind]
category = Category(prediction=class_ind, confidence=class_confidence, description=class_description)
category = Category(prediction=class_ind, confidence=softmax_predictions, description=class_description)

return category

Expand Down
3 changes: 1 addition & 2 deletions src/opendr/perception/skeleton_based_action_recognition/spatio_temporal_gcn_learner.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -529,10 +529,9 @@ def infer(self, SkeletonSeq_batch):

m = nn.Softmax(dim=0)
softmax_predictions = m(output.data[0])
class_confidence = float(torch.max(softmax_predictions))
class_ind = int(torch.argmax(softmax_predictions))
class_description = self.classes_dict[class_ind]
category = Category(prediction=class_ind, confidence=class_confidence, description=class_description)
category = Category(prediction=class_ind, confidence=softmax_predictions, description=class_description)

return category

Expand Down