histogram ggplot2

Poj2559 Largest Rectangle in a Histogram DescriptionA histogram is a polygon composed of a sequence of rectangles aligned at a common base line. the rectangles have equal widths but may have different heights. for example, the figure on the left shows the histogram that consists of rectangles with the heights 2, 1, 4, 5, 1, 3, 3, measured in units where 1 is the

Largest Rectangle in a histogram http://poj.org/problem?id=2559 Time limit:1000ms Memory limit:65536k Description A histogram is a polygon composed of a sequence of rectangles aligned in a common base line. The rectangles have equal widths but may have different. For example, the "figure on" the left shows the histogram, consists of rectangles with the Heigh

The project recently used a variety of charts, originally intended to use a third party, such as Mpandroid, this is a very powerful chart library, the application is very convenient, but finally found and design is not the same, no way, can only write their own. Today will be a written column of the demo posted here, the histogram can be based on the function of the data a few points: 1. According to the number of data, the dynamic plot of the pillar

The Tensorboard histogram dashboard shows how the distribution of some tensor in the TensorFlow graph changes over time. It is visualized by displaying many histograms of tensor at different points in time. One, see a basic example A normally-distributed variable, a normal distribution value. The mean changes over time.We use the tf.random_normal operation directly. Perfect solution.Of course, you also use the tensorboard,summary operation to populate

DescriptionA histogram is a polygon composed of a sequence of rectangles aligned at a common base line. the rectangles have equal widths but may have different heights. for example, the figure on the left shows the histogram that consists of rectangles with the heights 2, 1, 4, 5, 1, 3, 3, measured in units where 1 is the width of the rectangles: Usually, histograms are used to represent discrete distribu

Objective Image enhancement processing technology has been a very important basic image processing technology in the field of image processing. By taking appropriate enhancements, the original images that were blurred or even indistinguishable could be processed into a clear, clear and rich in useful information of the use of target images, so this kind of image processing technology in medicine, remote sensing, microbiology, criminal investigation and military and many other scientific researc

Find the rectangle with the largest area in the Histogram DescriptionA histogram is a polygon composed of a sequence of rectangles aligned at a common base line. the rectangles have equal widths but may have different heights. for example, the figure on the left shows the histogram that consists of rectangles with the heights 2, 1, 4, 5, 1, 3, 3, measured in unit

HOG (histograms of oriented gradients) gradient direction histogramThe directional gradient histogram (histogram of oriented Gradient, HOG) is a feature descriptor used for object detection in computer vision and image processing. This method uses the gradient direction characteristics of the image itself, similar to the edge direction histogram method, the SIFT

The content of this digital image histogram is the same, but it is implemented in mat format ~ Create a gray histogram // Draw the gray histogram int main () {mat SRC, gray; src = imread ("baboon.jpg"); cvtcolor (SRC, gray, cv_rgb2gray); int bins = 256; int hist_size [] = {bins}; float range [] = {0,256}; const float * ranges [] = {range}; matnd hist; int channel

the first approach to the adaptive histogram equalization is to divide the image into non-overlapping area blocks, and then make the histogram equalization for each block separately. If the image is noisy, the noise will be amplified in the block of each segmented small area.To avoid the effect of noise on image equalization, the adaptive Histogram equalization w

After one day, it was a black screen, and finally found that it was caused by a local variable. It is basically divided into three steps, which is to achieve a balanced histogram under the grayscale image. The color is directly balanced and researched and then supplemented. Step 1: Calculate the initial histogram, that is, the number of occurrences of each pixel. Int hist [256] = {0 }; For (INT y = 0; y {F

This is my first blog. I wrote a grayscale histogram equalization implemented by opencv. Please indicate the author and source for reprinting. Thank you! //////////////////////////////////////// /// // Project_name: gray Image Process: hist/Time: 2012-02-14 // Author: hellmonky /////////////////////////////////////// /// // # include Original grayscale image: Corresponding histogram: Images after

Largest rectangle in a Histogram Time Limit: 2000/1000 MS (Java/others) memory limit: 65536/32768 K (Java/Others)Total submission (s): 11137 accepted submission (s): 3047 Problem descriptiona histogram is a polygon composed of a sequence of rectangles aligned at a common base line. the rectangles have equal widths but may have different heights. for example, the figure on the left shows the

// Histogram balancing Bool histogramequalize (unsigned char * pdata, unsigned int nwidth, unsigned int nheight) { If (pdata = NULL) return false; Unsigned int x, y, I; Unsigned int linestart; Unsigned int histogram [256]; Unsigned int maptable [256]; Unsigned int tempvalue; // Obtain the Histogram For (I = 0; I { Histogram