glibvision/cv2_utils.py

import cv2
import numpy as np

#2024-11-27 add copy image
#2024-12-04 plot_text = False,plot line first
#2024-11-30 copy paste
def draw_bbox(image,box,color=(255,0,0),thickness=1):
  if thickness==0:
    return
  
  left = int(box[0])
  top = int(box[1])
  right = int(box[0]+box[2])
  bottom = int(box[1]+box[3])
  box_points =[(left,top),(right,top),(right,bottom),(left,bottom)]
  
  cv2.polylines(image, [np.array(box_points)], isClosed=True, color=color, thickness=thickness)


def to_int_points(points):
  int_points=[]
  for point in points:
    int_points.append([int(point[0]),int(point[1])])
  return int_points

def draw_text(img, text, point, font_scale=0.5, color=(200, 200, 200), thickness=1):
  font = cv2.FONT_HERSHEY_SIMPLEX
  cv2.putText(img, str(text), point, font, font_scale, color, thickness, cv2.LINE_AA)

plot_text_color = (200, 200, 200)
plot_text_font_scale = 0.5
plot_index = 1
plot_text = False

def set_plot_text(is_plot,text_font_scale,text_color):
  global plot_index,plot_text,plot_text_font_scale,plot_text_color
  plot_text = is_plot
  plot_index = 1
  plot_text_font_scale = text_font_scale
  plot_text_color = text_color

def plot_points(image,points,isClosed=False,circle_size=3,circle_color=(255,0,0),line_size=1,line_color=(0,0,255)):
    
    global plot_index,plot_text
    int_points = to_int_points(points)
    if line_size>0:
      cv2.polylines(image, [np.array(int_points)], isClosed=isClosed, color=line_color, thickness=line_size)
    if circle_size>0:
      for point in int_points:
        cv2.circle(image,point,circle_size,circle_color,-1)
        if plot_text:
          draw_text(image,plot_index,point,plot_text_font_scale,plot_text_color)
        plot_index+=1
    

def fill_points(image,points,thickness=1,line_color=(255,255,255),fill_color = (255,255,255)):
    np_points = np.array(points,dtype=np.int32)
    cv2.fillPoly(image, [np_points], fill_color)
    cv2.polylines(image, [np_points], isClosed=True, color=line_color, thickness=thickness)

def get_image_size(cv2_image):
    return cv2_image.shape[:2]

def get_channel(np_array):
    return np_array.shape[2] if np_array.ndim == 3 else 1 

def get_numpy_text(np_array,key=""):
    channel = get_channel(np_array)
    return f"{key} shape = {np_array.shape} channel = {channel} ndim = {np_array.ndim} size = {np_array.size}"


def gray3d_to_2d(grayscale: np.ndarray) -> np.ndarray:
    channel = get_channel(grayscale)
    if channel!=1:
        raise ValueError(f"color maybe rgb or rgba {get_numpy_text(grayscale)}")
    """
    3 次元グレースケール画像 (チャンネル数 1) を 2 次元に変換する。

    Args:
        grayscale (np.ndarray): 3 次元グレースケール画像 (チャンネル数 1)。

    Returns:
        np.ndarray: 2 次元グレースケール画像。
    """

    if grayscale.ndim == 2:
        return grayscale
    return np.squeeze(grayscale)

def blend_rgb_images(image1: np.ndarray, image2: np.ndarray, mask: np.ndarray) -> np.ndarray:
    """
    2 つの RGB 画像をマスク画像を使用してブレンドする。

    Args:
        image1 (np.ndarray): 最初の画像 (RGB)。
        image2 (np.ndarray): 2 番目の画像 (RGB)。
        mask (np.ndarray): マスク画像 (グレースケール)。

    Returns:
        np.ndarray: ブレンドされた画像 (RGB)。

    Raises:
        ValueError: 入力画像の形状が一致しない場合。
    """

    if image1.shape != image2.shape or image1.shape[:2] != mask.shape:
        raise ValueError("入力画像の形状が一致しません。")

    # 画像を float 型に変換
    image1 = image1.astype(float)
    image2 = image2.astype(float)

    # マスクを 3 チャンネルに変換し、0-1 の範囲にスケール
    alpha = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR).astype(float) / 255.0

    # ブレンド計算
    blended = (1 - alpha) * image1 + alpha * image2

    return blended.astype(np.uint8)

def create_color_image(img,color=(255,255,255)):
    mask = np.zeros_like(img)
    
    h, w = img.shape[:2]
    cv2.rectangle(mask, (0, 0), (w, h), color, -1)
    return mask

def pil_to_bgr_image(image):
  np_image = np.array(image, dtype=np.uint8)
  if np_image.shape[2] == 4:
      bgr_img = cv2.cvtColor(np_image, cv2.COLOR_RGBA2BGRA)
  else:
      bgr_img = cv2.cvtColor(np_image, cv2.COLOR_RGB2BGR)
  return bgr_img

def bgr_to_rgb(np_image):
  if np_image.shape[2] == 4:
      bgr_img = cv2.cvtColor(np_image, cv2.COLOR_RBGRA2RGBA)
  else:
      bgr_img = cv2.cvtColor(np_image, cv2.COLOR_BGR2RGB)
  return bgr_img

def copy_image(img1: np.ndarray, img2: np.ndarray, x: int, y: int) -> None:
    # チャネル数と次元数のチェック
    if img1.ndim != 3 or img2.ndim != 3:
        raise ValueError("Both img1 and img2 must be 3-dimensional arrays.")
    elif img1.shape[2] != img2.shape[2]:
        raise ValueError(f"img1 and img2 must have the same number of channels. img1 has {img1.shape[2]} channels, but img2 has {img2.shape[1]} channels.")

    # Type check
    if not isinstance(img1, np.ndarray) or not isinstance(img2, np.ndarray):
        raise TypeError("img1 and img2 must be NumPy arrays.")

    if x>=0:
      offset_x=0
      w = min(img1.shape[1]-x,img2.shape[1])
    else:
      w = min(img1.shape[1],img2.shape[1]+x)
      offset_x=int(-x)
      x = 0

    if y>=0:
      h = min(img1.shape[0]-y,img2.shape[0])
      offset_y=0
    else:
      h = min(img1.shape[0]-y,img2.shape[0]+y)
      offset_y=int(-y)
      y = 0
    x=int(x)
    y=int(y)
    h=int(h)
    w=int(w)
   
    
    print(f"img1 {img1.shape} img2{img2.shape} x={x} y={y} w={w} h={h}")
    # Paste the overlapping part
    img1[y:y+h, x:x+w] = img2[offset_y:h+offset_y, offset_x:w+offset_x]

def crop(image,bbox):
   x,y,width,height = bbox
   return image[y:y+height, x:x+width]
#not check safe
def paste(image,replace_image,x,y):
   height,width = replace_image.shape[:2]
   image[y:y+height, x:x+width] = replace_image