技术问询：face_recognition.face_landmarks是否支持CNN模式

Hey there! Great question—let's break this down clearly:

Short answer: The face_recognition.face_landmarks() method itself doesn't directly accept a "CNN mode" parameter, but you can absolutely use CNN-based face detection to power your landmark extraction. Here's how it works:

The face_landmarks() function relies on pre-detected face locations to extract facial landmarks. The face detection step (finding where faces are in the image) is handled separately by face_recognition.face_locations(), which does support both HOG (default, faster) and CNN (more accurate, slower) models.

Step-by-step code example using CNN mode: #

First, use CNN to detect face positions, then pass those positions to face_landmarks():

import face_recognition

# Load your target image
image = face_recognition.load_image_file("test.jpg")

# Detect face locations using CNN model
cnn_face_locations = face_recognition.face_locations(image, model="cnn")

# Extract landmarks using the CNN-detected face positions
face_landmarks_list = face_recognition.face_landmarks(image, face_locations=cnn_face_locations)

# Print out the results (optional)
for landmarks in face_landmarks_list:
    print("Found facial landmarks for this face:")
    for feature, points in landmarks.items():
        print(f"- {feature}: {points}")

Why this matters: #

Using the CNN model for face detection is helpful in trickier scenarios—like low-resolution images, faces at angles, or faces partially obscured. It's slower than the default HOG model, but trades speed for accuracy when you need it.

内容的提问来源于stack exchange，提问作者user2106796