hiResFix - resize based on the loger side of the image and keep aspect

[hortom]

Hi, is it possible to add another resize mode to this node? Something like "by longer side (keep aspect)"

It would require one parameter which is the target size of the longer_side, and the calculation would be something like this:

        if current_width > current_height:
            new_width, new_height = longer_side, int(current_height * longer_side / current_width)
        else:
            new_width, new_height = int(current_width * longer_side / current_height), longer_side

This would be useful because in the case you change the generated image aspect ratio and/or the size too, still the node would resize to the same dimension without any change of the parameters. I admit that maybe it wouldn't be beneficial to everyone but please consider adding this. :)

[TinyTerra]

Just pushed an update to the hiResFix node, hopefully that functions how you wanted it to. :)

[hortom]

Amazing! Thank you!

Looks like that the enforce_mul_of_64() function can receive a non-integer and return a non-integer. I pasted the whole error:

Error occurred when executing ttN hiresfixScale:

upsample_bilinear2d(): argument 'output_size' must be tuple of ints, but found element of type float at pos 2

File "e:\comfyUI\ComfyUI\execution.py", line 141, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "e:\comfyUI\ComfyUI\execution.py", line 75, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "e:\comfyUI\ComfyUI\execution.py", line 68, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "E:\comfyUI\ComfyUI\custom_nodes\ComfyUI_tinyterraNodes\tinyterraNodes.py", line 1579, in upscale
s = comfy.utils.common_upscale(samples, width, height, rescale_method, crop)
File "e:\comfyUI\ComfyUI\comfy\utils.py", line 168, in common_upscale
return torch.nn.functional.interpolate(s, size=(height, width), mode=upscale_method)
File "e:\comfyUI\python_embeded\lib\site-packages\torch\nn\functional.py", line 3959, in interpolate
return torch._C._nn.upsample_bilinear2d(input, output_size, align_corners, scale_factors)

This fixed it - I added int(): (from line 1573)

                if orig_width > orig_height:
                    width, height = longer_side, enforce_mul_of_64(int(longer_side * orig_height / orig_width))
                else:
                    width, height = enforce_mul_of_64(int(longer_side * orig_width / orig_height)), longer_side

Solution 2 could be to convert the received value d in enforce_mul_of_64(d).

[TinyTerra]

Oh right, forgot to stage the function changes - pushed again