getpixel函数是用来获取图像中某一点的像素的RGB颜色值，getpixel的参数是一个坐标点。对于图象的不同的模式，getpixel函数返回的值有所不同。...1.RGB模式 from PIL import Image im=Image.open('d:/22.jpg') print(im.mode) print(im.getpixel((0,0))) 结果为...as plt img = Image.open("D:\image_for_test\Spee.jpg") plt.imshow(img) plt.show() print(img.getpixel(...(0,0)),img.getpixel((178,298))) 结果： ?...到此这篇关于Python的PIL库中getpixel方法的使用的文章就介绍到这了,更多相关Python getpixel内容请搜索ZaLou.Cn以前的文章或继续浏览下面的相关文章希望大家以后多多支持ZaLou.Cn
+ img.getpixel((x, y + 1)) + img.getpixel((x + 1, y)) + img.getpixel((x + 1, y + 1)) return...img.getpixel((x, y - 1)) + img.getpixel((x - 1, y - 1)) + img.getpixel((x + 1, y - 1)) return...y - 1)) + cur_pixel + img.getpixel((x, y + 1)) + img.getpixel((x + 1, y - 1)) + img.getpixel((x + 1,...# 右边非顶点 sum_8 = img.getpixel((x, y - 1)) + cur_pixel + img.getpixel((x, y + 1)) + img.getpixel...- 1, y)) + img.getpixel((x - 1, y + 1)) + img.getpixel((x, y - 1)) + cur_pixel + img.getpixel((x, y
- 1: # 右上顶点 sum = cur_pixel + img.getpixel((x, y + 1)) + img.getpixel((x - 1, y)) + img.getpixel(...1, y + 1)) + cur_pixel + img.getpixel((x, y + 1)) + img.getpixel((x + 1, y)) + img.getpixel((x +...- 1: # 右下顶点 sum = cur_pixel + img.getpixel((x, y - 1)) + img.getpixel((x - 1, y)) + img.getpixel(...((x + 1, y)) + img.getpixel((x, y - 1)) + img.getpixel((x - 1, y - 1)) + img.getpixel((x + 1, y -...+ img.getpixel((x, y + 1)) + img.getpixel((x + 1, y - 1)) + img.getpixel((x + 1, y)) + img.getpixel
(x - 1, y - 1).R; p[1] = this.bitmap.GetPixel(x, y - 1).R; p[...2] = this.bitmap.GetPixel(x + 1, y - 1).R; p[3] = this.bitmap.GetPixel(x - 1, y)....R; p[4] = this.bitmap.GetPixel(x, y).R; p[5] = this.bitmap.GetPixel...(x + 1, y).R; p[6] = this.bitmap.GetPixel(x - 1, y + 1).R; p[...7] = this.bitmap.GetPixel(x, y + 1).R; p[8] = this.bitmap.GetPixel(x + 1, y + 1).
((0,0)) lena_1.getpixel((10,10)) lena_1.getpixel((10,120)) lena_1.getpixel((130,120))...example： lena_P = lena.convert("P") lena_P.mode 'P' lena_P.getpixel((0,0)) 结果： ?...lena_I = lena.convert("I") lena_I.mode 'I' lena_I.getpixel((0,0)) lena_I.getpixel((0,1))...lena_L = lena.convert("L") lena_L.getpixel((0,0)) lena_L.getpixel((0,1)) 从实验的结果看，模式“I”与模式...lena_F = lena.convert("F") lena_F.mode 'F' lena_F.getpixel((0,0)) 162.2429962158203 lena_F.getpixel
((x, y + 1)) \ + img.getpixel((x + 1, y)) \ + img.getpixel((x + 1...+ img.getpixel((x, y + 1)) \ + img.getpixel((x + 1, y)) \ + img.getpixel...+ img.getpixel((x + 1, y - 1)) \ + img.getpixel((x + 1, y)) \ + img.getpixel...+ img.getpixel((x - 1, y - 1)) \ + img.getpixel((x - 1, y)) \ + img.getpixel...+ img.getpixel((x, y + 1)) \ + img.getpixel((x + 1, y - 1)) \ + img.getpixel
(i - 1, j - 1).R < dgGrayValue) nearDots++; if (bmpobj.GetPixel(i, j - 1)...if (bmpobj.GetPixel(i - 1, j + 1).R < dgGrayValue) nearDots++; if (bmpobj.GetPixel...bmpobj.GetPixel(x + 1, y - 1).R; p[3] = bmpobj.GetPixel(x - 1, y).R; ...p[4] = bmpobj.GetPixel(x, y).R; p[5] = bmpobj.GetPixel(x + 1, y).R; ...p[6] = bmpobj.GetPixel(x - 1, y + 1).R; p[7] = bmpobj.GetPixel(x, y + 1).R;
blnGet1) { Color c = bitmap.GetPixel(x, intTop);...blnGet2) { Color c = bitmap.GetPixel(x, intBottom);...blnGet1) { Color c = bitmap.GetPixel(x, intTop);...blnGet1) { Color c = bitmap.GetPixel(intLeft, y);...blnGet1) { Color c = bitmap.GetPixel(intLeft, y);
) { //向左 如果为1返回 如果不是1 计算当前值 如果不在范围内设为1返回 并且向下递归 if (Math.Abs(bmp.GetPixel...int j = 0; j < bmp.Height; j++) { map.SetPixel(i + 1, j + 1, bmp.GetPixel... colors = new Stack(); colors.Push(new Point(x,y)); int colorB = map.GetPixel... x--; if (flag[x, y] == 0) { if (Math.Abs(map.GetPixel... y--; if (flag[x, y] == 0) { if (Math.Abs(map.GetPixel
从左向右扫描 for w in range(width): #从下向上扫描 for h in range(height): #获取图像指定位置的像素颜色 color = im.getpixel...height, im): #从右向左扫描 for w in range(width-1, -1, -1): for h in range(height): color = im.getpixel...width, height, im): for h in range(height-1, -1, -1): for w in range(width): color = im.getpixel...searchBottom(width, height, im): for h in range(height): for w in range(width): color = im.getpixel
(y+col) = srcImage->GetHeight()) pixel = srcImage->GetPixel...(x,y); else pixel = srcImage->GetPixel(x + row,y + col);...(y+col) = srcImage->GetHeight()) pixel = srcImage->GetPixel...(x,y); else pixel = srcImage->GetPixel(x + row,y + col);...GetHeight();y++) { int r = 0,g = 0,b = 0; COLORREF pixel = srcImage->GetPixel
pixel = srcImage->GetPixel(x,y); ? else ? ...pixel = srcImage->GetPixel(x + row,y + col); ? ...pixel = srcImage->GetPixel(x,y); ? else ? ...pixel = srcImage->GetPixel(x + row,y + col); ? ...COLORREF pixel = srcImage->GetPixel(x,y); ? //r += GetRValue(pixel); ?
R=[] G=[] B=[] a,b = hide.size for x in range(a): for y in range(b): R.append(bin(hide.getpixel...((x,y))[0]).replace('0b','').zfill(8)) G.append(bin(hide.getpixel((x, y))[1]).replace('0b',''...).zfill(8)) B.append(bin(hide.getpixel((x, y))[2]).replace('0b','').zfill(8)) R1=[] G1=[] B1=...((x,y))[0]).replace('0b','').zfill(8)) G.append(bin(p.getpixel((x, y))[1]).replace('0b', '')....zfill(8)) B.append(bin(p.getpixel((x, y))[2]).replace('0b', '').zfill(8)) R1=[] G1=[] B1=[]
bitmap = BitmapFactory.decodeResource(getResources(), R.mipmap.iv_200x200); int color_0_0 = bitmap.getPixel...); return null; } return filePic.getAbsolutePath(); } ---- 3.bitmap.getPixel...int pixel_0_0 = bitmap.getPixel(0, 0); int pixel_1_0 = bitmap.getPixel(1, 0); int pixel_0_1 = bitmap.getPixel...(0, 1); int pixel_1_1 = bitmap.getPixel(1, 1); 黑：pixel_0_0:-16777216 红：pixel_1_0:-65536 白：pixel...ball.y = j * d + d / 2; //获取像素点的a、r、g、b int color_i_j = bitmap.getPixel
im.size[0]): for h in range(im.size[1]): #生成器推导式，计算所有临时图像中对应位置上像素值的平均值 r = sum((tempIm.getpixel...((w,h))[0] for tempIm in ims)) // num g = sum((tempIm.getpixel((w,h))[1] for tempIm in ims...)) // num b = sum((tempIm.getpixel((w,h))[2] for tempIm in ims)) // num #写入结果图像中对应位置...expectedRatio = 0.05 for w in range(width): for h in range(height): #获取两个图像同一位置上的像素值 c1 = im1.getpixel...((w,h)) c2 = im2.getpixel((w,h)) #生成器推导式，判断两个像素值各分量之差的绝对值是否小于阈值 similar = (abs
int i = x; i < xx; i++) { for (int k = y;k < yy;k++) { int color = bitmap.getPixel...Bitmap bitmap = BitmapFactory.decodeFile(path);//新建并实例化bitmap对象 int color = bitmap.getPixel...Bitmap bitmap = BitmapFactory.decodeFile(path);//新建并实例化bitmap对象 int color = bitmap.getPixel...Bitmap bitmap = BitmapFactory.decodeFile(path);//新建并实例化bitmap对象 int color = bitmap.getPixel...123/testDemo.png"; Bitmap bitmap = BitmapFactory.decodeFile(path); int color = bitmap.getPixel
BitmapFactory .decodeResource(getResources(), R.mipmap.iv_200x200); //获取第1行，第1个像素颜色 int color_0_0 = bitmap.getPixel...int pixel_0_0 = bitmap.getPixel(0, 0); int pixel_1_0 = bitmap.getPixel(1, 0); int pixel_0_1 = bitmap.getPixel...(0, 1); int pixel_1_1 = bitmap.getPixel(1, 1); 黑：pixel_0_0:-16777216 红：pixel_1_0:-65536 白：pixel...ball.y = j * d + d / 2; //获取像素点的a、r、g、b int color_i_j = bitmap.getPixel...ball.vY = rangeInt(-15, 35); ball.aY = 0.98f; ball.color = bitmap.getPixel
bitmap.getHeight(); h++) { boolean holdBlackPix = false; for (int w = 0; w < bitmap.getWidth(); w++) { if (bitmap.getPixel...bitmap.getWidth(); w++) { boolean holdBlackPix = false; for (int h = 0; h < bitmap.getHeight(); h++) { if (bitmap.getPixel...= 0; w--) { boolean holdBlackPix = false; for (int h = 0; h < bitmap.getHeight(); h++) { if (bitmap.getPixel...= 0; h--) { boolean holdBlackPix = false; for (int w = 0; w < bitmap.getWidth(); w++) { if (bitmap.getPixel...; h < top + cropHeight; h++) { for (int w = left; w < left + cropWidth; w++) { newPix[i++] = bitmap.getPixel
在DataBuffer层次结构类型中，定义方法GetPixel()和GetLengthl()。...; public const int TYPE_INT = 4; public const int TYPE_USHORT = 5; public abstract int GetPixel...return idata.Length; } } public class DataBufferByte : DataBuffer { public override int GetPixel...sdata = (short[])inData; return sdata.Length; } } 并将客户程序switch语句及其case语句简化为： int pixel = GetPixel...(inData); int length = GetLength(inData); 由于引用dataBuffer指向的是传入的DataBuffer子类对象，因此上述语句将调用相应子类的GetPixel(
continue if _w_ == w and _h_ == h: continue if img_obj.getpixel...img.show() # 尝试去掉红像素点 w, h = img.size for _w in range(w): for _h in range(h): o_pixel = img.getpixel...if _w == 0 or _w == w-1 or 0 == _h or _h == h-1: return 0 p_round_items = [img.getpixel...( (_w, _h-1)), img.getpixel((_w, _h+1)), img.getpixel((_w-1, _h)), img.getpixel((_w+1, _h...img.size for _w in range(w): for _h in range(h): o_pixel = img.getpixel
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