Our Facial Landmarks Detection API provides an advanced solution for detecting and analyzing facial landmarks with high precision. This API supports the detection of 72, 150, and 201 key points, covering essential facial features such as eyes, eyebrows, lips, and nose contours. Additionally, it offers precise localization of facial features, including eyebrows, eyes, nose, mouth, and cheeks, as well as accurate identification of facial contours for both single and multiple faces. The API also includes face angle estimation, allowing for the determination of various facial poses in the image. Ideal for developers in the fields of photography, augmented reality, and biometric security, this API enables enhanced facial recognition and image processing capabilities. Integrate our Facial Landmarks Detection API into your application to provide users with robust and precise facial analysis tools, improving the accuracy and functionality of your facial recognition and image editing solutions.
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truncated for documentation purposes"}
curl --location 'https://zylalabs.com/api/4439/facial+landmarks+api/5452/facial+landmarks' \
--header 'Content-Type: application/json' \
--form 'image=@"FILE_PATH"'
| Header | Description |
|---|---|
Authorization
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[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
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Our Facial Landmarks Detection API provides an advanced solution for detecting and analyzing facial landmarks with high precision. This API supports the detection of 72, 150, and 201 key points, covering essential facial features such as eyes, eyebrows, lips, and nose contours. Additionally, it offers precise localization of facial features, including eyebrows, eyes, nose, mouth, and cheeks, as well as accurate identification of facial contours for both single and multiple faces. The API also includes face angle estimation, allowing for the determination of various facial poses in the image.
Facial Recognition: Enhancing the accuracy of facial recognition systems by identifying key facial features. Animation and Gaming: Creating realistic facial animations by mapping facial landmarks for character models. Augmented Reality (AR): Enabling AR applications to accurately place virtual elements on users’ faces, such as filters and masks. Beauty and Cosmetics: Powering virtual makeup and beauty apps to apply cosmetics accurately on facial features. Photography and Videography: Improving facial detection for better focusing and exposure settings in cameras.
High Precision: Provides accurate identification of key facial features, enhancing the effectiveness of applications relying on facial analysis. Real-Time Processing: Capable of identifying facial landmarks in real time, making it suitable for live applications such as AR and security monitoring. Versatility: Applicable to various fields, including facial recognition, animation, AR, medical diagnostics, beauty, photography, security, and human-computer interaction. Consistency: Delivers reliable and consistent results across different faces and conditions.
Computer Vision Researchers and Engineers: Professionals and academics who work on developing facial recognition systems, emotion detection algorithms, and other applications requiring precise facial landmark localization. Augmented Reality (AR) and Virtual Reality (VR) Developers: Individuals creating immersive experiences that involve facial tracking and interaction. Healthcare Practitioners and Researchers: Those studying facial anatomy for medical diagnosis, facial reconstruction, or facial expression analysis in psychological research. Digital Artists and Animators: Creators who use facial landmarks for character animation, facial morphing, and other visual effects.
The Facial Landmarks API returns data related to facial features, including the number of detected faces, their locations, face tokens, confidence levels, and detailed landmark coordinates. It also provides additional information such as age, gender, and facial angles.
Key fields in the response include `face_num` (number of faces detected), `face_list` (details of each face), `face_probability` (confidence score), and various landmark arrays (e.g., `landmark4`, `landmark72`, etc.) that provide coordinates for facial features.
The response data is structured as a JSON object containing public parameters (like `request_id` and `error_code`) and business parameters (like `result`, which includes face details). Each face's information is nested within the `face_list` array.
The endpoint accepts parameters such as `image` (required), `max_face_num` (optional, to specify the number of faces to detect), and `face_field` (optional, to request additional information like age and gender).
Users can customize requests by adjusting the `max_face_num` to detect multiple faces and selecting specific `face_field` values to retrieve additional data, such as `landmark150` or `gender`, based on their application needs.
The API provides information on facial landmarks, face locations, confidence scores, age, gender, and facial angles. Users can choose to receive varying levels of detail by specifying the `face_field` parameter.
Users can utilize the returned data by analyzing the `face_list` for facial feature coordinates, using `face_probability` for confidence assessments, and leveraging age and gender data for demographic insights in applications like marketing or security.
Typical use cases include enhancing facial recognition systems, developing AR applications with real-time facial tracking, creating personalized beauty filters, and conducting demographic analysis in user engagement studies.
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