"TypeError: Cannot handle this data type: (1, 1, 5), |u1" when ran in img2img

[nyqui]

numpy 1.23.3 onnx 1.13.1 onnxruntime 1.14.1 opencv-python 4.7.0.72 Pillow 9.4.0

This script runs fine in txt2img, but I can't get it to work in img2img. Not sure how the process would differ between the two.

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Traceback (most recent call last): File "C:\Stable Diffusion\venv\lib\site-packages\PIL\Image.py", line 3080, in fromarray mode, rawmode = _fromarray_typemap[typekey] KeyError: ((1, 1, 5), '|u1')

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "C:\Stable Diffusion\modules\call_queue.py", line 56, in f res = list(func(*args, *kwargs)) File "C:\Stable Diffusion\modules\call_queue.py", line 37, in f res = func(args, *kwargs) File "C:\Stable Diffusion\modules\img2img.py", line 170, in img2img processed = modules.scripts.scripts_img2img.run(p, args) File "C:\Stable Diffusion\modules\scripts.py", line 407, in run processed = script.run(p, *script_args) File "C:\Stable Diffusion\extensions\ABG_extension\scripts\app.py", line 125, in run img = im.fromarray(nimg) File "C:\Stable Diffusion\venv\lib\site-packages\PIL\Image.py", line 3083, in fromarray raise TypeError(msg) from e TypeError: Cannot handle this data type: (1, 1, 5), |u1

[coudys]

I have the same isse, any image type, in img2img tab

[gsurus]

The error is caused by the image shape being incorrect, in the extensions Scripts\app.py file, modify the file starting on line 125

from img = im.fromarray(nimg)

to

# Check the number of channels in the nimg array
num_channels = nimg.shape[2]
if num_channels > 4:
# Select only the first 3 or 4 channels (RGB or RGBA)
    nimg = nimg[:, :, :4]

# Ensure the data type is uint8

nimg = nimg.astype(np.uint8)
# Convert the image back to a format that can be saved

img = im.fromarray(nimg)

[nyqui]

The error is caused by the image shape being incorrect, in the extensions Scripts\app.py file, modify the file starting on line 125

from img = im.fromarray(nimg)

to

# Check the number of channels in the nimg array
num_channels = nimg.shape[2]
if num_channels > 4:
# Select only the first 3 or 4 channels (RGB or RGBA)
    nimg = nimg[:, :, :4]

# Ensure the data type is uint8

nimg = nimg.astype(np.uint8)
# Convert the image back to a format that can be saved

img = im.fromarray(nimg)

That worked nicely. Thank you.