openmv/usr/examples/face_eye_detection.py
Kwabena W. Agyeman bcd5151412 New drawing functions.
All the drawing functions have been updated to handle automatic clipping
when drawing offscren and work with both grayscale and RGB565.
Additionally, all functions now accept color arguments.

I've also updated the example scripts with the new functions and tested
them out to make sure they work.

Additionally, I wrote a test suite for the drawing functions to make
sure they work.
2016-02-18 22:40:12 -05:00

47 lines
1.5 KiB
Python

import sensor, time, image
# Reset sensor
sensor.reset()
# Sensor settings
sensor.set_contrast(1)
sensor.set_gainceiling(16)
sensor.set_framesize(sensor.HQVGA)
sensor.set_pixformat(sensor.GRAYSCALE)
# Load Haar Cascade
# By default this will use all stages, lower satges is faster but less accurate.
face_cascade = image.HaarCascade("frontalface", stages=25)
eyes_cascade = image.HaarCascade("eye", stages=24)
print(face_cascade, eyes_cascade)
# FPS clock
clock = time.clock()
while (True):
clock.tick()
# Capture snapshot
img = sensor.snapshot()
# Find a face !
# Note: Lower scale factor scales-down the image more and detects smaller objects.
# Higher threshold results in a higher detection rate, with more false positives.
objects = img.find_features(face_cascade, threshold=0.5, scale=1.5)
# Draw faces
for face in objects:
img.draw_rectangle(face)
# Now find eyes within each face.
# Note: Use a higher threshold here (more detections) and lower scale (to find small objects)
eyes = img.find_features(eyes_cascade, threshold=0.65, scale=1.25, roi=face)
for e in eyes:
e = [face[0]+e[0], face[1]+e[1], e[2], e[3]] # Add face offset
img.draw_rectangle(e)
# Draw crosshair, add width/2 and height/2
img.draw_cross(e[0]+int(e[2]/2), e[1]+int(e[3]/2))
# Print FPS.
# Note: Actual FPS is higher, streaming the FB makes it slower.
print(clock.fps())