From 09dfcc42776357cdeba43e6a897cdbc8b9367c08 Mon Sep 17 00:00:00 2001 From: user1 Date: Thu, 20 Jul 2023 00:38:20 -0700 Subject: [PATCH] Added pixel_perfect_resolution() method to controlnet_utils.py, but not using yet. To be usable this will likely require modification of ControlNet preprocessors --- invokeai/app/util/controlnet_utils.py | 56 ++++++++++++++++++++++++++- 1 file changed, 55 insertions(+), 1 deletion(-) diff --git a/invokeai/app/util/controlnet_utils.py b/invokeai/app/util/controlnet_utils.py index 67fd7bb43e..342fa147c5 100644 --- a/invokeai/app/util/controlnet_utils.py +++ b/invokeai/app/util/controlnet_utils.py @@ -94,12 +94,66 @@ def nake_nms(x): return y +################################################################################ +# copied from Mikubill/sd-webui-controlnet external_code.py and modified for InvokeAI +################################################################################ +# FIXME: not using yet, if used in the future will most likely require modification of preprocessors +def pixel_perfect_resolution( + image: np.ndarray, + target_H: int, + target_W: int, + resize_mode: str, +) -> int: + """ + Calculate the estimated resolution for resizing an image while preserving aspect ratio. + + The function first calculates scaling factors for height and width of the image based on the target + height and width. Then, based on the chosen resize mode, it either takes the smaller or the larger + scaling factor to estimate the new resolution. + + If the resize mode is OUTER_FIT, the function uses the smaller scaling factor, ensuring the whole image + fits within the target dimensions, potentially leaving some empty space. + + If the resize mode is not OUTER_FIT, the function uses the larger scaling factor, ensuring the target + dimensions are fully filled, potentially cropping the image. + + After calculating the estimated resolution, the function prints some debugging information. + + Args: + image (np.ndarray): A 3D numpy array representing an image. The dimensions represent [height, width, channels]. + target_H (int): The target height for the image. + target_W (int): The target width for the image. + resize_mode (ResizeMode): The mode for resizing. + + Returns: + int: The estimated resolution after resizing. + """ + raw_H, raw_W, _ = image.shape + + k0 = float(target_H) / float(raw_H) + k1 = float(target_W) / float(raw_W) + + if resize_mode == "fill_resize": + estimation = min(k0, k1) * float(min(raw_H, raw_W)) + else: # "crop_resize" or "just_resize" (or possibly "just_resize_simple"?) + estimation = max(k0, k1) * float(min(raw_H, raw_W)) + + # print(f"Pixel Perfect Computation:") + # print(f"resize_mode = {resize_mode}") + # print(f"raw_H = {raw_H}") + # print(f"raw_W = {raw_W}") + # print(f"target_H = {target_H}") + # print(f"target_W = {target_W}") + # print(f"estimation = {estimation}") + + return int(np.round(estimation)) + + ########################################################################### # Copied from detectmap_proc method in scripts/detectmap_proc.py in Mikubill/sd-webui-controlnet # modified for InvokeAI ########################################################################### # def detectmap_proc(detected_map, module, resize_mode, h, w): -@staticmethod def np_img_resize( np_img: np.ndarray, resize_mode: str,