import random import numpy as np from PIL import Image, ImageEnhance, ImageFilter def binarize_mask(mask, threshold=0): return mask.point(lambda p: 255 if p > threshold else 0).convert("L") def square_crop_by_mask(image, mask, scale=1.2): W, H = image.size bbox = mask.getbbox() if bbox is None: cx, cy = W / 2.0, H / 2.0 side = float(min(W, H)) else: l, u, r, lo = bbox cx = (l + r) / 2.0 cy = (u + lo) / 2.0 side = max(r - l, lo - u) * scale side_i = max(1, int(round(side))) left = int(round(cx - side_i / 2.0)) top = int(round(cy - side_i / 2.0)) box = (left, top, left + side_i, top + side_i) # PIL fills out-of-bounds crop regions with 0: black for the RGB image and # "unmasked" (0) for the L mask - exactly the black padding we want. return image.crop(box), mask.crop(box), box def process_source(source_image, source_mask, image_size=1024, crop_scale=1.2, binarize_threshold=0): source_mask = binarize_mask(source_mask, binarize_threshold) source_image_c, source_mask_c, crop_box = square_crop_by_mask(source_image, source_mask, crop_scale) size = (image_size, image_size) image = source_image_c.resize(size, Image.LANCZOS) # GT crop mask = source_mask_c.resize(size, Image.NEAREST) white = Image.new("RGB", size, (255, 255, 255)) # composite(white, image, mask): mask==255 -> white, mask==0 -> image background_image = Image.composite(white, image, mask) return background_image, image, crop_box, source_mask_c def process_reference(ref_image, ref_mask, image_size=1024, crop_scale=1.2, binarize_threshold=0, augment=False, p_aug=0.8): ref_mask = binarize_mask(ref_mask, binarize_threshold) ref_image_c, ref_mask_c, _ = square_crop_by_mask(ref_image, ref_mask, crop_scale) size = (image_size, image_size) ref_image_r = ref_image_c.resize(size, Image.LANCZOS) ref_mask_r = ref_mask_c.resize(size, Image.NEAREST) white = Image.new("RGB", size, (255, 255, 255)) # composite(ref_image, white, mask): mask==255 -> object, mask==0 -> white ref_image_out = Image.composite(ref_image_r, white, ref_mask_r) if augment: ref_image_out = augment_ref_image(ref_image_out, ref_mask_r, p_aug=p_aug) return ref_image_out def paste_back(generated_crop, source_image, crop_box, source_mask_cropped, feather=0): left, top, right, bottom = crop_box crop_side = right - left generated_crop = generated_crop.resize((crop_side, crop_side), Image.LANCZOS) original_crop = source_image.crop(crop_box) if feather > 0: source_mask_cropped = source_mask_cropped.filter(ImageFilter.GaussianBlur(feather)) edited_crop = Image.composite(generated_crop, original_crop, source_mask_cropped) final_image = source_image.copy() final_image.paste(edited_crop, (left, top)) return final_image def _adjust_hue(img, shift): """Shift the hue of an RGB image by ``shift`` (in 0..255 units).""" hsv = img.convert("HSV") h, s, v = hsv.split() h_arr = (np.asarray(h).astype(np.int16) + int(round(shift))) % 256 h = Image.fromarray(h_arr.astype(np.uint8), "L") return Image.merge("HSV", (h, s, v)).convert("RGB") def augment_ref_image(ref_image, mask, p_aug=0.8): img = ref_image.convert("RGB").copy() m = mask.convert("L") # Horizontal flip is safe: the object sits on a uniform white background. if random.random() < 0.5: img = img.transpose(Image.FLIP_LEFT_RIGHT) m = m.transpose(Image.FLIP_LEFT_RIGHT) # Colour jitter on the whole image; background is re-whitened below. if random.random() < p_aug: img = ImageEnhance.Brightness(img).enhance(random.uniform(0.85, 1.15)) if random.random() < p_aug: img = ImageEnhance.Contrast(img).enhance(random.uniform(0.85, 1.15)) if random.random() < p_aug: img = ImageEnhance.Color(img).enhance(random.uniform(0.85, 1.15)) if random.random() < p_aug: img = ImageEnhance.Sharpness(img).enhance(random.uniform(0.9, 1.1)) if random.random() < p_aug: img = _adjust_hue(img, random.uniform(-0.06, 0.06) * 255.0) # Keep the (jittered) object, reset everything outside the mask to white. white = Image.new("RGB", img.size, (255, 255, 255)) return Image.composite(img, white, m)