from fastplotlib.widgets import ImageWidget
import cv2
import pims

a = pims.open("img.tiff") # array-like of shape [n_frames, x, y]
vid = pims.open("vid.avi") # array-like of shape [n_frames, x, y, rgb_channels]

# produces a slider for each axis passed to `slider_axes`
# additional kwargs are passed to `graphics.Image`, such as `cmap`
iw = ImageWidget(data=a, slider_axes=0, axis_order="txy", **kwargs)
# could also specify slider axis from one of the axis_order indicators
# this could be the default kwarg for slider_axes
iw = ImageWidget(data=a, slider_axes="t", axis_order="txy", **kwargs)
iw.show() # returns `VBox` of `ImageWidget` and `ipywidgets.IntSlider`

# multiple sliders
iw = ImageWidget(data=a, slider_axes=["t", "z"], axis_order="tzxy", **kwargs)

# pass a frame apply function that is applied to the frame array when `update_frame()` is called
to_gray = lambda rgb_frame: cv2.cvtColor(rgb_frame, cv2.COLOR_BGR2GRAY)
iw_vid = ImageWidget(data=b, slider_axes=0, frame_apply=to_gray)

# Same widget but with gridplot, pass list of array-like
iw_grid = ImageWidget(
    data=[a, b], 
    slider_axes=0,  # use 0th axis for a single slider for both arrays
    frame_apply={b: to_gray}
)
iw_grid.show()

# if a.shape[0] != b.shape[0] it can print a warning and just not update `a` when it goes out of bounds for it, but continue updating `b`

# create multiple sliders for different dimensions
iw_grid_async = ImageWidget(
    data=[a, b],
    slider_axes=["t", "z"],
    axes_order={a: "tzxy", b: "xyzt"},
    slice_avg={"t": 10, "z": 1},  # window size for slice averaging along some axes
    frame_apply={b: to_gray}
)
iw_grid_async.show()