# Image Patches Absolute Optical Flow Translation # # This example shows off using your OpenMV Cam to measure translation # in the X and Y direction by comparing the current and a previous # image against each other. Note that only X and Y translation is # handled - not rotation/scale in this mode. # # However, this examples goes beyond doing optical flow on the whole # image at once. Instead it breaks up the process by working on groups # of pixels in the image. This gives you a "new" image of results. # # NOTE that surfaces need to have some type of "edge" on them for the # algorithm to work. A featureless surface produces crazy results. BLOCK_W = 16 # pow2 BLOCK_H = 16 # pow2 # To run this demo effectively please mount your OpenMV Cam on a steady # base and SLOWLY translate it to the left, right, up, and down and # watch the numbers change. Note that you can see displacement numbers # up +- half of the hoizontal and vertical resolution. import sensor, image, time # NOTE!!! You have to use a small power of 2 resolution when using # find_displacement(). This is because the algorithm is powered by # something called phase correlation which does the image comparison # using FFTs. A non-power of 2 resolution requires padding to a power # of 2 which reduces the usefulness of the algorithm results. Please # use a resolution like B128X128 or B128X64 (2x faster). # Your OpenMV Cam supports power of 2 resolutions of 64x32, 64x64, # 128x64, and 128x128. If you want a resolution of 32x32 you can create # it by doing "img.pool(2, 2)" on a 64x64 image. sensor.reset() # Reset and initialize the sensor. sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to GRAYSCALE (or RGB565) sensor.set_framesize(sensor.B128X128) # Set frame size to 128x128... (or 128x64)... sensor.skip_frames(time = 2000) # Wait for settings take effect. clock = time.clock() # Create a clock object to track the 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. extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.GRAYSCALE) extra_fb.replace(sensor.snapshot()) while(True): clock.tick() # Track elapsed milliseconds between snapshots(). img = sensor.snapshot() # Take a picture and return the image. for y in range(0, sensor.height(), BLOCK_H): for x in range(0, sensor.width(), BLOCK_W): # For this example we never update the old image to measure absolute change. displacement = extra_fb.find_displacement(img, \ roi = (x, y, BLOCK_W, BLOCK_H), template_roi = (x, y, BLOCK_W, BLOCK_H)) # Below 0.1 or so (YMMV) and the results are just noise. if(displacement.response() > 0.1): pixel_x = x + (BLOCK_W//2) + int(displacement.x_translation()) pixel_y = y + (BLOCK_H//2) + int(displacement.y_translation()) img.draw_line((x + BLOCK_W//2, y + BLOCK_H//2, pixel_x, pixel_y), \ color = 255) else: img.draw_line((x + BLOCK_W//2, y + BLOCK_H//2, x + BLOCK_W//2, y + BLOCK_H//2), \ color = 0) print(clock.fps())