Detect Faces: Boxes, Landmarks, and Counts in One Call If you've ever tried to ship a "crop to face" feature, a privacy blur before user uploads go public, or a simple head-count on event photos, you already know the pain. Most face-detection options out there are either overkill — bundled into a full recognition product you don't need — or so bare that you end up making a second call just to figure out where the eyes are. We built detect-faces to sit exactly in that gap. What it does POST /v1/image/detect-faces takes a public image URL and gives you back, for every face in the image: A bounding box — the rectangle around the face, so you can crop, blur, or mask it. Key landmarks — coordinates for the eyes, nose, and mouth, so you can centre crops, align portraits, or build downstream alignment logic without a second round trip. A per-face confidence score , so you can tune precision vs recall for your use case. The request itself is small. You send three fields: image_url — a public URL of the image.…