scripts/examples: Fix Haar Cascade Paths.

This commit is contained in:
Kwabena W. Agyeman 2025-05-30 10:46:44 -07:00
parent 8069b2a966
commit de2bea26e9
15 changed files with 17 additions and 17 deletions

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@ -27,7 +27,7 @@ led = machine.LED("LED_RED")
# HaarCascade are loaded. However, You can adjust the number of stages to speed
# up processing at the expense of accuracy. The frontalface HaarCascade has 25
# stages.
face_cascade = image.HaarCascade("frontalface", stages=25)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
while True:
print("About to start detecting faces...")

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@ -33,7 +33,7 @@ led = machine.LED("LED_RED")
# HaarCascade are loaded. However, You can adjust the number of stages to speed
# up processing at the expense of accuracy. The frontalface HaarCascade has 25
# stages.
face_cascade = image.HaarCascade("frontalface", stages=25)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
while True:
print("About to start detecting faces...")

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@ -11,7 +11,7 @@
import image
import time
stream = image.ImageIO("/stream.bin", "r")
stream = image.ImageIO("stream.bin", "r")
clock = time.clock() # Create a clock object to track the FPS.
while True:

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@ -23,7 +23,7 @@ sensor.skip_frames(time=2000) # Wait for settings take effect.
clock = time.clock() # Create a clock object to track the FPS.
led = machine.LED("LED_RED")
stream = image.ImageIO("/stream.bin", "w")
stream = image.ImageIO("stream.bin", "w")
# Red LED on means we are capturing frames.
led.on()

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@ -34,7 +34,7 @@ led = machine.LED("LED_RED")
# HaarCascade are loaded. However, You can adjust the number of stages to speed
# up processing at the expense of accuracy. The frontalface HaarCascade has 25
# stages.
face_cascade = image.HaarCascade("frontalface", stages=25)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
while True:
print("About to start detecting faces...")

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@ -10,7 +10,7 @@ import image
import time
# Load image
img = image.Image("/example.bmp", copy_to_fb=True)
img = image.Image("example.bmp", copy_to_fb=True)
# Add a small delay to allow the IDE to read the loaded image.
time.sleep_ms(1000)

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@ -31,7 +31,7 @@ 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)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
print(face_cascade)
# FPS clock

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@ -23,8 +23,8 @@ 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)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
eyes_cascade = image.HaarCascade("/rom/haarcascade_eye.cascade", stages=24)
print(face_cascade, eyes_cascade)
# FPS clock

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@ -26,7 +26,7 @@ sensor.skip_frames(time=2000)
# Load Haar Cascade
# By default this will use all stages, lower satges is faster but less accurate.
face_cascade = image.HaarCascade("frontalface", stages=25)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
print(face_cascade)
# First set of keypoints

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@ -32,7 +32,7 @@ sensor.set_pixformat(sensor.GRAYSCALE)
# Load Haar Cascade
# By default this will use all stages, lower stages is faster but less accurate.
eyes_cascade = image.HaarCascade("eye", stages=24)
eyes_cascade = image.HaarCascade("/rom/haarcascade_eye.cascade", stages=24)
print(eyes_cascade)
# FPS clock

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@ -27,7 +27,7 @@ while True:
img.find_hog()
# Uncomment to save raw FB to file and exit the loop
# img.save("/hog.pgm")
# img.save("hog.pgm")
# break
print(clock.fps())

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@ -34,7 +34,7 @@ def draw_keypoints(img, kpts):
kpts1 = None
# NOTE: uncomment to load a keypoints descriptor from file
# kpts1 = image.load_descriptor("/desc.orb")
# kpts1 = image.load_descriptor("desc.orb")
# img = sensor.snapshot()
# draw_keypoints(img, kpts1)

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@ -26,7 +26,7 @@ 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)
face_cascade = image.HaarCascade("/rom/haarcascade_frontalface.cascade", stages=25)
print(face_cascade)
# Skip a few frames to allow the sensor settle down
@ -36,7 +36,7 @@ for i in range(0, 30):
img.draw_string(0, 0, "Please wait...")
d0 = None
# d0 = image.load_descriptor("/desc.lbp")
# d0 = image.load_descriptor("desc.lbp")
clock = time.clock()
while True:

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@ -33,7 +33,7 @@ sensor.set_pixformat(sensor.GRAYSCALE)
# Load template.
# Template should be a small (eg. 32x32 pixels) grayscale image.
template = image.Image("/template.pgm")
template = image.Image("template.pgm")
clock = time.clock()

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@ -123,7 +123,7 @@ def face_detection(data):
faces = (
sensor.snapshot()
.gamma_corr(contrast=1.5)
.find_features(image.HaarCascade("frontalface"))
.find_features(image.HaarCascade("/rom/haarcascade_frontalface.cascade"))
)
if not faces:
return bytes() # No detections.