OpenMV IDE出现MemoryError: FB Alloc Collision错误求助

First off, let's break down what that error means: 'MemoryError: FB Alloc Collision' is OpenMV's way of telling you it ran out of frame buffer memory while trying to process your image. The find_circles() function is pretty memory-intensive—it needs to analyze pixel data and store intermediate results, and if your camera's frame size is too big or the algorithm is generating too many candidate circles, it can overwhelm the device's limited RAM.

Here are practical fixes to get your code working:

1. Reduce the camera's frame resolution #

The biggest memory hog is usually the raw image data. Shrink the frame size to cut down on memory usage right away. Add this setup code before your loop:

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565)  # RGB565 uses half the memory of RGB888
sensor.set_framesize(sensor.QVGA)     # QVGA (320x240) is smaller than VGA (640x480)
sensor.skip_frames(time = 2000)

Go even smaller (like sensor.QQVGA) if you don't need high detail—this will free up tons of memory for circle detection.

2. Tune the find_circles() parameters to reduce processing load #

Your current threshold is 1600, which might be low enough to detect way too many false circles (each detected circle uses memory). Try increasing the threshold, and tweak the margin parameters to reduce redundant detections:

# Higher threshold = fewer candidate circles; adjust based on your use case
for c in img.find_circles(threshold = 2500, x_margin = 20, y_margin = 20, r_margin = 20):
    img.draw_circle(c.x(), c.y(), c.r(), color=(255,0,0))
    print(c)

The margin parameters control how close two circles can be before they're merged—larger margins mean fewer circles to process.

3. Optimize loop operations to save memory #

Printing every detected circle to the serial port can also slow things down and indirectly use memory. If you don't need real-time prints, limit how often you output, or switch to printing only key info:

count = 0
for c in img.find_circles(threshold = 2500, x_margin = 20, y_margin = 20, r_margin = 20):
    img.draw_circle(c.x(), c.y(), c.r(), color=(255,0,0))
    count += 1
    # Print only every 10 frames to reduce overhead
    if count % 10 == 0:
        print(f"Detected circle: {c}")

4. Manually trigger garbage collection #

OpenMV uses MicroPython, which has automatic garbage collection, but sometimes you need to give it a nudge. Import the gc module and call gc.collect() periodically to free up unused memory:

import gc

# ... your setup code ...

while True:
    img = sensor.snapshot()
    gc.collect()  # Run garbage collection before circle detection
    for c in img.find_circles(threshold = 2500, x_margin = 20, y_margin = 20, r_margin = 20):
        img.draw_circle(c.x(), c.y(), c.r(), color=(255,0,0))
        print(c)

Start with reducing the frame size first—that's the most impactful fix for this error. If you still run into issues, try combining multiple tweaks above.

内容的提问来源于stack exchange，提问作者Chase