import cv2 import numpy as np import mp_triangles import time from PIL import Image from glibvision.cv2_utils import blend_rgb_images,pil_to_bgr_image,fill_points,crop,paste from mp_utils import get_pixel_cordinate_list,extract_landmark,get_pixel_cordinate,get_normalized_landmarks,sort_triangles_by_depth,get_landmark_bbox import numba as nb @nb.jit(nopython=True, parallel=True) def blend_rgb_images_numba(image1, image2, mask): height, width, _ = image1.shape result = np.empty((height, width, 3), dtype=np.float32) for i in nb.prange(height): for j in range(width): alpha = mask[i, j] / 255.0 for k in range(3): result[i, j, k] = (1 - alpha) * image1[i, j, k] + alpha * image2[i, j, k] return result.astype(np.uint8) @nb.jit(nopython=True, parallel=True) def blend_rgba_images_numba(image1, image2, mask): assert image1.shape[2] == image2.shape[2] , f"Input images must be same image1 = {image1.shape[2]} image2 ={image2.shape[2]}" channel = image1.shape[2] height, width, _ = image1.shape result = np.empty((height, width, channel), dtype=np.float32) for i in nb.prange(height): for j in range(width): alpha = mask[i, j] / 255.0 for k in range(channel): result[i, j, k] = (1 - alpha) * image1[i, j, k] + alpha * image2[i, j, k] return result.astype(np.uint8) """ https://stackoverflow.com/questions/6946653/copying-triangular-image-region-with-pil This topic give me a idea """ """ bug some hide value make white """ debug_affinn = False min_affin_plus = 0.1 def apply_affine_transformation_to_triangle(src_tri, dst_tri, src_img, dst_img): src_tri_np = np.float32(src_tri) dst_tri_np = np.float32(dst_tri) assert src_tri_np.shape == (3, 2), f"src_tri_np の形状が不正 {src_tri_np.shape}" assert dst_tri_np.shape == (3, 2), f"dst_tri_np の形状が不正 {dst_tri_np.shape}" #trying avoid same value,or M will broken if (src_tri_np[0] == src_tri_np[1]).all(): src_tri_np[0]+=min_affin_plus if (src_tri_np[0] == src_tri_np[2]).all(): src_tri_np[0]+=min_affin_plus if (src_tri_np[1] == src_tri_np[2]).all(): src_tri_np[1]+=min_affin_plus if (src_tri_np[1] == src_tri_np[0]).all(): src_tri_np[1]+=min_affin_plus if (src_tri_np[1] == src_tri_np[0]).all() or (src_tri_np[1] == src_tri_np[2]).all() or (src_tri_np[2] == src_tri_np[0]).all(): print("same will white noise happen") # 透視変換行列の計算 M = cv2.getAffineTransform(src_tri_np, dst_tri_np) # 画像のサイズ h_src, w_src = src_img.shape[:2] h_dst, w_dst = dst_img.shape[:2] # 元画像から三角形領域を切り抜くマスク生成 #src_mask = np.zeros((h_src, w_src), dtype=np.uint8) #cv2.fillPoly(src_mask, [np.int32(src_tri)], 255) # Not 元画像の三角形領域のみをマスクで抽出 src_triangle = src_img #cv2.bitwise_and(src_img, src_img, mask=src_mask) # 変換行列を使って元画像の三角形領域を目標画像のサイズへ変換 transformed = cv2.warpAffine(src_triangle, M, (w_dst, h_dst)) if debug_affinn: cv2.imwrite('affin_src.jpg', src_triangle) cv2.imwrite('affin_transformed.jpg', transformed) #print(f"dst_img={dst_img.shape}") #print(f"transformed={transformed.shape}") # 変換後のマスクの生成 dst_mask = np.zeros((h_dst, w_dst), dtype=np.uint8) cv2.fillPoly(dst_mask, [np.int32(dst_tri)], 255) # 目標画像のマスク領域をクリアするためにデストのインバートマスクを作成 #dst_mask_inv = cv2.bitwise_not(dst_mask) # 目標画像のマスク部分をクリア #dst_background = cv2.bitwise_and(dst_img, dst_img, mask=dst_mask_inv) # 変換された元画像の三角形部分と目標画像の背景部分を合成 #dst_img = cv2.add(dst_background, transformed) #s = time.time() #dst_img = blend_rgb_images(dst_img,transformed,dst_mask) use_blend_rgb = False if use_blend_rgb: if src_img.shape[2] == 3: dst_img = blend_rgb_images_numba(dst_img,transformed,dst_mask) else: dst_img = blend_rgba_images_numba(dst_img,transformed,dst_mask) else: dst_mask_inv = cv2.bitwise_not(dst_mask) transformed = cv2.bitwise_and(transformed, transformed, mask=dst_mask) dst_img = cv2.bitwise_and(dst_img, dst_img, mask=dst_mask_inv) dst_img = cv2.add(dst_img, transformed) # TODO add rgb mode #print(f"blend {time.time() -s}") if debug_affinn: cv2.imwrite('affin_transformed_masked.jpg', transformed) cv2.imwrite('affin_dst_mask.jpg', dst_mask) return dst_img from skimage.exposure import match_histograms def color_match(base_image,cropped_image,color_match_format="RGB"): reference = np.array(base_image.convert(color_match_format)) target =np.array(cropped_image.convert(color_match_format)) matched = match_histograms(target, reference,channel_axis=-1) return Image.fromarray(matched,mode=color_match_format) def process_landmark_transform(image,transform_target_image, innner_mouth,innner_eyes, color_matching=False,transparent_background=False,add_align_mouth=False,add_align_eyes=False,blur_size=0): image_h,image_w = image.shape[:2] align_h,align_w = transform_target_image.shape[:2] mp_image,image_face_landmarker_result = extract_landmark(image) image_larndmarks=image_face_landmarker_result.face_landmarks image_bbox = get_landmark_bbox(image_larndmarks,image_w,image_h,16,16) mp_image,align_face_landmarker_result = extract_landmark(transform_target_image) align_larndmarks=align_face_landmarker_result.face_landmarks align_bbox = get_landmark_bbox(align_larndmarks,align_w,align_h,16,16) if color_matching: image_cropped = crop(image,image_bbox) target_cropped = crop(transform_target_image,align_bbox) matched = match_histograms(image_cropped, target_cropped,channel_axis=-1) paste(image,matched,image_bbox[0],image_bbox[1]) landmark_points = get_normalized_landmarks(align_larndmarks) mesh_triangle_indices = mp_triangles.mesh_triangle_indices.copy()#using directly sometime share #always mix for blur mesh_triangle_indices += mp_triangles.INNER_MOUTH mesh_triangle_indices += mp_triangles.INNER_LEFT_EYES + mp_triangles.INNER_RIGHT_EYES #print(mesh_triangle_indices) sort_triangles_by_depth(landmark_points,mesh_triangle_indices) #mesh_triangle_indices = mp_triangles.contour_to_triangles(True,draw_updown_contour) + mp_triangles.contour_to_triangles(False,draw_updown_contour)+ mp_triangles.mesh_triangle_indices triangle_size = len(mesh_triangle_indices) print(f"triangle_size = {triangle_size},time ={0.1*triangle_size}") s = time.time() need_transparent_way = transparent_background == True or blur_size > 0 if need_transparent_way:# convert Alpha transparent_image = np.zeros_like(cv2.cvtColor(transform_target_image, cv2.COLOR_BGR2BGRA)) h, w = transparent_image.shape[:2] cv2.rectangle(transparent_image, (0, 0), (w, h), (0,0,0,0), -1) applied_image = transparent_image image = cv2.cvtColor(image, cv2.COLOR_BGR2BGRA) else: applied_image = transform_target_image for i in range(0,triangle_size):# triangle_indices = mesh_triangle_indices[i] image_points = get_pixel_cordinate_list(image_larndmarks,triangle_indices,image_w,image_h) align_points = get_pixel_cordinate_list(align_larndmarks,triangle_indices,align_w,align_h) #print(image_points) #print(align_points) #fill_points(image,image_points,thickness=3,fill_color=(0,0,0,0)) #s = time.time() #print(f"applied_image={applied_image.shape}") applied_image=apply_affine_transformation_to_triangle(image_points,align_points,image,applied_image) print(f"take time {time.time()-s}") if need_transparent_way: blur_radius = blur_size if blur_radius!=0 and blur_radius%2 == 0: blur_radius+=1 b, g, r,a = cv2.split(applied_image) applied_image = cv2.merge([b,g,r]) mask = a.copy() dilate = blur_radius kernel = np.ones((dilate, dilate), np.uint8) mask = cv2.erode(mask, kernel, iterations=1) if blur_radius>0: blurred_image = cv2.GaussianBlur(mask, (blur_radius, blur_radius), 0) #should be odd else: blurred_image = mask if transparent_background: #transform_target_image = np.zeros_like(cv2.cvtColor(transform_target_image, cv2.COLOR_BGR2BGRA)) transform_target_image=cv2.cvtColor(transform_target_image, cv2.COLOR_BGR2BGRA) applied_image = cv2.merge([b,g,r,blurred_image]) else: applied_image = blend_rgb_images(transform_target_image,applied_image,blurred_image) # after mix if not innner_mouth or not innner_eyes or (transparent_background and (add_align_mouth or add_align_eyes)): import mp_constants dst_mask = np.zeros((align_h,align_w), dtype=np.uint8) if not innner_mouth or (transparent_background and add_align_mouth): mouth_cordinates = get_pixel_cordinate_list(align_larndmarks,mp_constants.LINE_INNER_MOUTH,align_h,align_w) cv2.fillPoly(dst_mask, [np.int32(mouth_cordinates)], 255) if (transparent_background and not add_align_mouth): cv2.fillPoly(transform_target_image, [np.int32(mouth_cordinates)], [0,0,0,0]) if not innner_eyes or (transparent_background and add_align_eyes): left_eyes_cordinates = get_pixel_cordinate_list(align_larndmarks,mp_constants.LINE_LEFT_INNER_EYES,align_h,align_w) cv2.fillPoly(dst_mask, [np.int32(left_eyes_cordinates)], 255) right_eyes_cordinates = get_pixel_cordinate_list(align_larndmarks,mp_constants.LINE_RIGHT_INNER_EYES,align_h,align_w) cv2.fillPoly(dst_mask, [np.int32(right_eyes_cordinates)], 255) if (transparent_background and not add_align_eyes): cv2.fillPoly(transform_target_image, [np.int32(left_eyes_cordinates)], [0,0,0,0]) cv2.fillPoly(transform_target_image, [np.int32(right_eyes_cordinates)], [0,0,0,0]) #cv2.imwrite("deb_transform_target_image.jpg",transform_target_image) #cv2.imwrite("deb_dst_mask.jpg",dst_mask) #cv2.imwrite("deb_applied_image.jpg",applied_image) applied_image = blend_rgba_images_numba(applied_image,transform_target_image,dst_mask) return applied_image def process_landmark_transform_pil(pil_image,pil_align_target_image, innner_mouth,innner_eyes, color_matching=False,transparent_background=False,add_align_mouth=False,add_align_eyes=False,blur_size=0): image = pil_to_bgr_image(pil_image) align_target_image = pil_to_bgr_image(pil_align_target_image) cv_result = process_landmark_transform(image,align_target_image,innner_mouth,innner_eyes,color_matching,transparent_background,add_align_mouth,add_align_eyes,blur_size) if transparent_background: return Image.fromarray(cv2.cvtColor(cv_result, cv2.COLOR_BGRA2RGBA)) else: return Image.fromarray(cv2.cvtColor(cv_result, cv2.COLOR_BGR2RGB)) if __name__ == "__main__": #image = Image.open('examples/00002062.jpg') #align_target = Image.open('examples/02316230.jpg') image = cv2.imread('examples/02316230.jpg') # 元画像 align_target = cv2.imread('examples/00003245_00.jpg') # 目標画像 result_img = process_landmark_transform(image,align_target) cv2.imshow('Transformed Image', result_img) cv2.waitKey(0) cv2.destroyAllWindows() cv2.imwrite('align.png', result_img)