mirror of
https://github.com/openmv/openmv.git
synced 2025-11-04 14:49:50 +08:00
Add frame differencing example scripts.
Better ones that can work in memory now.
This commit is contained in:
parent
27f5110ab7
commit
a6b659131d
@ -0,0 +1,65 @@
|
|||||||
|
# Advanced Frame Differencing Example
|
||||||
|
#
|
||||||
|
# This example demonstrates using frame differencing with your OpenMV Cam. This
|
||||||
|
# example is advanced because it preforms a background update to deal with the
|
||||||
|
# backgound image changing overtime.
|
||||||
|
|
||||||
|
import sensor, image, pyb, os, time
|
||||||
|
|
||||||
|
TRIGGER_THRESHOLD = 5
|
||||||
|
|
||||||
|
BG_UPDATE_FRAMES = 50 # How many frames before blending.
|
||||||
|
BG_UPDATE_BLEND = 128 # How much to blend by... ([0-256]==[0.0-1.0]).
|
||||||
|
|
||||||
|
sensor.reset() # Initialize the camera sensor.
|
||||||
|
sensor.set_pixformat(sensor.RGB565) # or sensor.RGB565
|
||||||
|
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
||||||
|
sensor.skip_frames(time = 2000) # Let new settings take affect.
|
||||||
|
sensor.set_auto_whitebal(False) # Turn off white balance.
|
||||||
|
clock = time.clock() # Tracks FPS.
|
||||||
|
|
||||||
|
# Take from the main frame buffer's RAM to allocate a second frame buffer.
|
||||||
|
# There's a lot more RAM in the frame buffer than in the MicroPython heap.
|
||||||
|
# However, after doing this you have a lot less RAM for some algorithms...
|
||||||
|
# So, be aware that it's a lot easier to get out of RAM issues now. However,
|
||||||
|
# frame differencing doesn't use a lot of the extra space in the frame buffer.
|
||||||
|
# But, things like AprilTags do and won't work if you do this...
|
||||||
|
extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
|
||||||
|
|
||||||
|
print("About to save background image...")
|
||||||
|
sensor.skip_frames(time = 2000) # Give the user time to get ready.
|
||||||
|
extra_fb.replace(sensor.snapshot())
|
||||||
|
print("Saved background image - Now frame differencing!")
|
||||||
|
|
||||||
|
triggered = False
|
||||||
|
|
||||||
|
frame_count = 0
|
||||||
|
while(True):
|
||||||
|
clock.tick() # Track elapsed milliseconds between snapshots().
|
||||||
|
img = sensor.snapshot() # Take a picture and return the image.
|
||||||
|
|
||||||
|
frame_count += 1
|
||||||
|
if (frame_count > BG_UPDATE_FRAMES) and not triggered:
|
||||||
|
frame_count = 0
|
||||||
|
# Blend in new frame. We're doing 256-alpha here because we want to
|
||||||
|
# blend the new frame into the backgound. Not the background into the
|
||||||
|
# new frame which would be just alpha. Blend replaces each pixel by
|
||||||
|
# ((NEW*(alpha))+(OLD*(256-alpha)))/256. So, a low alpha results in
|
||||||
|
# low blending of the new image while a high alpha results in high
|
||||||
|
# blending of the new image. We need to reverse that for this update.
|
||||||
|
img.blend(extra_fb, alpha=(256-BG_UPDATE_BLEND))
|
||||||
|
extra_fb.replace(img)
|
||||||
|
|
||||||
|
# Replace the image with the "abs(NEW-OLD)" frame difference.
|
||||||
|
img.difference(extra_fb)
|
||||||
|
|
||||||
|
hist = img.get_histogram()
|
||||||
|
# This code below works by comparing the 99th percentile value (e.g. the
|
||||||
|
# non-outlier max value against the 90th percentile value (e.g. a non-max
|
||||||
|
# value. The difference between the two values will grow as the difference
|
||||||
|
# image seems more pixels change.
|
||||||
|
diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value()
|
||||||
|
triggered = diff > TRIGGER_THRESHOLD
|
||||||
|
|
||||||
|
print(clock.fps(), triggered) # Note: Your OpenMV Cam runs about half as fast while
|
||||||
|
# connected to your computer. The FPS should increase once disconnected.
|
||||||
@ -0,0 +1,47 @@
|
|||||||
|
# In Memory Basic Frame Differencing Example
|
||||||
|
#
|
||||||
|
# This example demonstrates using frame differencing with your OpenMV Cam. It's
|
||||||
|
# called basic frame differencing because there's no background image update.
|
||||||
|
# So, as time passes the background image may change resulting in issues.
|
||||||
|
|
||||||
|
import sensor, image, pyb, os, time
|
||||||
|
|
||||||
|
TRIGGER_THRESHOLD = 5
|
||||||
|
|
||||||
|
sensor.reset() # Initialize the camera sensor.
|
||||||
|
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
|
||||||
|
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
||||||
|
sensor.skip_frames(time = 2000) # Let new settings take affect.
|
||||||
|
sensor.set_auto_whitebal(False) # Turn off white balance.
|
||||||
|
clock = time.clock() # Tracks FPS.
|
||||||
|
|
||||||
|
# Take from the main frame buffer's RAM to allocate a second frame buffer.
|
||||||
|
# There's a lot more RAM in the frame buffer than in the MicroPython heap.
|
||||||
|
# However, after doing this you have a lot less RAM for some algorithms...
|
||||||
|
# So, be aware that it's a lot easier to get out of RAM issues now. However,
|
||||||
|
# frame differencing doesn't use a lot of the extra space in the frame buffer.
|
||||||
|
# But, things like AprilTags do and won't work if you do this...
|
||||||
|
extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
|
||||||
|
|
||||||
|
print("About to save background image...")
|
||||||
|
sensor.skip_frames(time = 2000) # Give the user time to get ready.
|
||||||
|
extra_fb.replace(sensor.snapshot())
|
||||||
|
print("Saved background image - Now frame differencing!")
|
||||||
|
|
||||||
|
while(True):
|
||||||
|
clock.tick() # Track elapsed milliseconds between snapshots().
|
||||||
|
img = sensor.snapshot() # Take a picture and return the image.
|
||||||
|
|
||||||
|
# Replace the image with the "abs(NEW-OLD)" frame difference.
|
||||||
|
img.difference(extra_fb)
|
||||||
|
|
||||||
|
hist = img.get_histogram()
|
||||||
|
# This code below works by comparing the 99th percentile value (e.g. the
|
||||||
|
# non-outlier max value against the 90th percentile value (e.g. a non-max
|
||||||
|
# value. The difference between the two values will grow as the difference
|
||||||
|
# image seems more pixels change.
|
||||||
|
diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value()
|
||||||
|
triggered = diff > TRIGGER_THRESHOLD
|
||||||
|
|
||||||
|
print(clock.fps(), triggered) # Note: Your OpenMV Cam runs about half as fast while
|
||||||
|
# connected to your computer. The FPS should increase once disconnected.
|
||||||
@ -0,0 +1,39 @@
|
|||||||
|
# Structural Similarity (SSIM) Example
|
||||||
|
#
|
||||||
|
# This example shows off how to use the SSIM algorithm on your OpenMV Cam
|
||||||
|
# to detect differences between two images. The SSIM algorithm compares
|
||||||
|
# 8x8 blocks of pixels between two images to determine a similarity
|
||||||
|
# score between two images.
|
||||||
|
|
||||||
|
import sensor, image, pyb, os, time
|
||||||
|
|
||||||
|
# The image has likely changed if the sim.min() is lower than this.
|
||||||
|
MIN_TRIGGER_THRESHOLD = -0.4
|
||||||
|
|
||||||
|
sensor.reset() # Initialize the camera sensor.
|
||||||
|
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
|
||||||
|
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
||||||
|
sensor.skip_frames(time = 2000) # Let new settings take affect.
|
||||||
|
sensor.set_auto_whitebal(False) # Turn off white balance.
|
||||||
|
clock = time.clock() # Tracks FPS.
|
||||||
|
|
||||||
|
# Take from the main frame buffer's RAM to allocate a second frame buffer.
|
||||||
|
# There's a lot more RAM in the frame buffer than in the MicroPython heap.
|
||||||
|
# However, after doing this you have a lot less RAM for some algorithms...
|
||||||
|
# So, be aware that it's a lot easier to get out of RAM issues now. However,
|
||||||
|
# frame differencing doesn't use a lot of the extra space in the frame buffer.
|
||||||
|
# But, things like AprilTags do and won't work if you do this...
|
||||||
|
extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
|
||||||
|
|
||||||
|
print("About to save background image...")
|
||||||
|
sensor.skip_frames(time = 2000) # Give the user time to get ready.
|
||||||
|
extra_fb.replace(sensor.snapshot())
|
||||||
|
print("Saved background image!")
|
||||||
|
|
||||||
|
while(True):
|
||||||
|
clock.tick() # Track elapsed milliseconds between snapshots().
|
||||||
|
img = sensor.snapshot() # Take a picture and return the image.
|
||||||
|
sim = img.get_similarity(extra_fb)
|
||||||
|
change = "- Change -" if sim.min() < MIN_TRIGGER_THRESHOLD else "- No Change -"
|
||||||
|
|
||||||
|
print(clock.fps(), change, sim)
|
||||||
@ -8,11 +8,13 @@
|
|||||||
|
|
||||||
import sensor, image, pyb, os, time
|
import sensor, image, pyb, os, time
|
||||||
|
|
||||||
|
TRIGGER_THRESHOLD = 5
|
||||||
|
|
||||||
BG_UPDATE_FRAMES = 50 # How many frames before blending.
|
BG_UPDATE_FRAMES = 50 # How many frames before blending.
|
||||||
BG_UPDATE_BLEND = 128 # How much to blend by... ([0-256]==[0.0-1.0]).
|
BG_UPDATE_BLEND = 128 # How much to blend by... ([0-256]==[0.0-1.0]).
|
||||||
|
|
||||||
sensor.reset() # Initialize the camera sensor.
|
sensor.reset() # Initialize the camera sensor.
|
||||||
sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.RGB565
|
sensor.set_pixformat(sensor.RGB565) # or sensor.RGB565
|
||||||
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
||||||
sensor.skip_frames(time = 2000) # Let new settings take affect.
|
sensor.skip_frames(time = 2000) # Let new settings take affect.
|
||||||
sensor.set_auto_whitebal(False) # Turn off white balance.
|
sensor.set_auto_whitebal(False) # Turn off white balance.
|
||||||
@ -25,13 +27,15 @@ sensor.skip_frames(time = 2000) # Give the user time to get ready.
|
|||||||
sensor.snapshot().save("temp/bg.bmp")
|
sensor.snapshot().save("temp/bg.bmp")
|
||||||
print("Saved background image - Now frame differencing!")
|
print("Saved background image - Now frame differencing!")
|
||||||
|
|
||||||
|
triggered = False
|
||||||
|
|
||||||
frame_count = 0
|
frame_count = 0
|
||||||
while(True):
|
while(True):
|
||||||
clock.tick() # Track elapsed milliseconds between snapshots().
|
clock.tick() # Track elapsed milliseconds between snapshots().
|
||||||
img = sensor.snapshot() # Take a picture and return the image.
|
img = sensor.snapshot() # Take a picture and return the image.
|
||||||
|
|
||||||
frame_count += 1
|
frame_count += 1
|
||||||
if frame_count > BG_UPDATE_FRAMES:
|
if (frame_count > BG_UPDATE_FRAMES) and not triggered:
|
||||||
frame_count = 0
|
frame_count = 0
|
||||||
# Blend in new frame. We're doing 256-alpha here because we want to
|
# Blend in new frame. We're doing 256-alpha here because we want to
|
||||||
# blend the new frame into the backgound. Not the background into the
|
# blend the new frame into the backgound. Not the background into the
|
||||||
@ -45,5 +49,13 @@ while(True):
|
|||||||
# Replace the image with the "abs(NEW-OLD)" frame difference.
|
# Replace the image with the "abs(NEW-OLD)" frame difference.
|
||||||
img.difference("temp/bg.bmp")
|
img.difference("temp/bg.bmp")
|
||||||
|
|
||||||
print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
|
hist = img.get_histogram()
|
||||||
|
# This code below works by comparing the 99th percentile value (e.g. the
|
||||||
|
# non-outlier max value against the 90th percentile value (e.g. a non-max
|
||||||
|
# value. The difference between the two values will grow as the difference
|
||||||
|
# image seems more pixels change.
|
||||||
|
diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value()
|
||||||
|
triggered = diff > TRIGGER_THRESHOLD
|
||||||
|
|
||||||
|
print(clock.fps(), triggered) # Note: Your OpenMV Cam runs about half as fast while
|
||||||
# connected to your computer. The FPS should increase once disconnected.
|
# connected to your computer. The FPS should increase once disconnected.
|
||||||
@ -8,6 +8,8 @@
|
|||||||
|
|
||||||
import sensor, image, pyb, os, time
|
import sensor, image, pyb, os, time
|
||||||
|
|
||||||
|
TRIGGER_THRESHOLD = 5
|
||||||
|
|
||||||
sensor.reset() # Initialize the camera sensor.
|
sensor.reset() # Initialize the camera sensor.
|
||||||
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
|
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
|
||||||
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
|
||||||
@ -29,5 +31,13 @@ while(True):
|
|||||||
# Replace the image with the "abs(NEW-OLD)" frame difference.
|
# Replace the image with the "abs(NEW-OLD)" frame difference.
|
||||||
img.difference("temp/bg.bmp")
|
img.difference("temp/bg.bmp")
|
||||||
|
|
||||||
print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
|
hist = img.get_histogram()
|
||||||
|
# This code below works by comparing the 99th percentile value (e.g. the
|
||||||
|
# non-outlier max value against the 90th percentile value (e.g. a non-max
|
||||||
|
# value. The difference between the two values will grow as the difference
|
||||||
|
# image seems more pixels change.
|
||||||
|
diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value()
|
||||||
|
triggered = diff > TRIGGER_THRESHOLD
|
||||||
|
|
||||||
|
print(clock.fps(), triggered) # Note: Your OpenMV Cam runs about half as fast while
|
||||||
# connected to your computer. The FPS should increase once disconnected.
|
# connected to your computer. The FPS should increase once disconnected.
|
||||||
Loading…
Reference in New Issue
Block a user