mirror of
https://github.com/openmv/openmv.git
synced 2025-11-04 14:49:50 +08:00
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
# Face Recognition
|
|
#
|
|
# Use this script to run a TensorFlow lite image classifier on faces detected within an image.
|
|
# The classifier is free to do facial recognition, expression detection, or whatever.
|
|
|
|
import sensor, image, time, tf
|
|
|
|
sensor.reset()
|
|
sensor.set_pixformat(sensor.RGB565)
|
|
sensor.set_framesize(sensor.QVGA)
|
|
sensor.skip_frames(time = 2000)
|
|
|
|
clock = time.clock()
|
|
|
|
net = tf.load("trained.tflite", load_to_fb=True)
|
|
labels = [l.rstrip('\n') for l in open("labels.txt")]
|
|
|
|
while(True):
|
|
clock.tick()
|
|
|
|
# Take a picture and brighten things up for the frontal face detector.
|
|
img = sensor.snapshot().gamma_corr(contrast=1.5)
|
|
|
|
# Returns a list of rects (x, y, w, h) where faces are.
|
|
faces = img.find_features(image.HaarCascade("frontalface"))
|
|
|
|
for f in faces:
|
|
|
|
# Classify a face and get the class scores list
|
|
scores = net.classify(img, roi=f)[0].output()
|
|
|
|
# Find the highest class score and lookup the label for that
|
|
label = labels[scores.index(max(scores))]
|
|
|
|
# Draw a box around the face
|
|
img.draw_rectangle(f)
|
|
|
|
# Draw the label above the face
|
|
img.draw_string(f[0]+3, f[1]-1, label, mono_space=False)
|
|
|
|
print(clock.fps())
|