openmv/usr/examples/09-Feature-Detection/keypoints.py
2017-01-15 18:43:14 +02:00

57 lines
2.0 KiB
Python

# Object tracking with keypoints example.
# Show the camera an object and then run the script. A set of keypoints will be extracted
# once and then tracked in the following frames. If you want a new set of keypoints re-run
# the script. NOTE: see the docs for arguments to tune find_keypoints and match_keypoints.
import sensor, time, image
# Reset sensor
sensor.reset()
# Sensor settings
sensor.set_contrast(1)
sensor.set_gainceiling(16)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((240, 240))
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_auto_gain(False, value=100)
sensor.skip_frames(30)
def draw_keypoints(img, kpts):
print(kpts)
img.draw_keypoints(kpts)
img = sensor.snapshot()
time.sleep(1000)
kpts1 = None
# NOTE: uncomment to load a keypoints descriptor from file
#kpts1 = image.load_descriptor("/desc.orb")
#img = sensor.snapshot()
#draw_keypoints(img, kpts1)
clock = time.clock()
while (True):
clock.tick()
img = sensor.snapshot()
if (kpts1 == None):
# NOTE: By default find_keypoints returns multi-scale keypoints extracted from an image pyramid.
kpts1 = img.find_keypoints(max_keypoints=150, threshold=20, scale_factor=1.1)
draw_keypoints(img, kpts1)
else:
# NOTE: When extracting keypoints to match the first descriptor, we use normalized=True to extract
# keypoints from the first scale only, which will match one of the scales in the first descriptor.
kpts2 = img.find_keypoints(max_keypoints=150, threshold=20, normalized=True)
if (kpts2):
c = image.match_descriptor(kpts1, kpts2, threshold=80)
match = c[6] # C[6] contains the number of matches.
if (match>5):
img.draw_rectangle(c[2:6])
img.draw_cross(c[0], c[1], size=10)
print(kpts2, "matched:%d dt:%d"%(match, c[7]))
# NOTE: uncomment if you want to draw the keypoints
#img.draw_keypoints(kpts2, size=KEYPOINTS_SIZE, matched=True)
# Draw FPS
img.draw_string(0, 0, "FPS:%.2f"%(clock.fps()))