OpenCV

Python OpenCV Box2D

由 久未见 提交于 2021-02-06 20:04:27
问题 I am trying to call OpenCV function MinAreaRect2 from within python. I use OpenCV 2.4.2 with python 2.7 and numpy 1.6. I went this far : import cv def nda2ipl(arr, dtype=None): return cv.fromarray(np.ascontiguousarray(arr, dtype=dtype)) def min_area_rect2(points): storage = cv.CreateMemStorage() cv_points = nda2ipl(points.reshape((-1, 1, 2))) out = cv.MinAreaRect2(cv_points, storage) return out I can call this function with a ndarray of shape (N x 2). I get this kind of results : ((476.5, 604

fps - how to divide count by time function to determine fps

由 浪尽此生 提交于 2021-02-06 16:22:46
问题 I have a counter working that counts every frame. what I want to do is divide this by time to determine the FPS of my program. But I'm not sure how to perform operations on timing functions within python. I've tried initializing time as fps_time = time.time fps_time = float(time.time) fps_time = np.float(time.time) fps_time = time() Then for calculating the fps, FPS = (counter / fps_time) FPS = float(counter / fps_time) FPS = float(counter (fps_time)) But errors I'm getting are object is not

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由 最后都变了- 提交于 2021-02-06 15:47:45
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opencv.js perspective transform

由 青春壹個敷衍的年華 提交于 2021-02-06 14:21:05
问题 I'm trying to use opencv.js to find a document in a provided image (detect edges, apply perspective transform, etc. I've got a reasonable set of code that (occasionally) detects edges of a document and grabs the bounding box for that. However, I'm struggling to do the perspective transform steps. There are some helpers for this (not in JS) here and here. Unfortunately I'm getting stuck on something simple. I can find the matching Mat that has 4 edges. Displaying that shows it to be accurate.

opencv.js perspective transform

由 ℡╲_俬逩灬. 提交于 2021-02-06 14:20:30
问题 I'm trying to use opencv.js to find a document in a provided image (detect edges, apply perspective transform, etc. I've got a reasonable set of code that (occasionally) detects edges of a document and grabs the bounding box for that. However, I'm struggling to do the perspective transform steps. There are some helpers for this (not in JS) here and here. Unfortunately I'm getting stuck on something simple. I can find the matching Mat that has 4 edges. Displaying that shows it to be accurate.

opencv.js perspective transform

由 我的未来我决定 提交于 2021-02-06 14:09:40
问题 I'm trying to use opencv.js to find a document in a provided image (detect edges, apply perspective transform, etc. I've got a reasonable set of code that (occasionally) detects edges of a document and grabs the bounding box for that. However, I'm struggling to do the perspective transform steps. There are some helpers for this (not in JS) here and here. Unfortunately I'm getting stuck on something simple. I can find the matching Mat that has 4 edges. Displaying that shows it to be accurate.

detect text in images with opencv

由 时光毁灭记忆、已成空白 提交于 2021-02-06 14:01:03
问题 I need to detect text in images.. Have some code here which works in most cases.. But not in all.. See attached input/output image code #include "string" #include "fstream" #include "/var/bin/opencv/include/opencv2/opencv.hpp" using namespace std; using namespace cv; void detect_text(string input){ Mat large = imread(input); Mat rgb; // downsample and use it for processing pyrDown(large, rgb); Mat small; cvtColor(rgb, small, CV_BGR2GRAY); // morphological gradient Mat grad; Mat morphKernel =

detect text in images with opencv

由 大憨熊 提交于 2021-02-06 13:55:32
问题 I need to detect text in images.. Have some code here which works in most cases.. But not in all.. See attached input/output image code #include "string" #include "fstream" #include "/var/bin/opencv/include/opencv2/opencv.hpp" using namespace std; using namespace cv; void detect_text(string input){ Mat large = imread(input); Mat rgb; // downsample and use it for processing pyrDown(large, rgb); Mat small; cvtColor(rgb, small, CV_BGR2GRAY); // morphological gradient Mat grad; Mat morphKernel =

Using inRange() in OpenCV to detect colors in a range

由 北慕城南 提交于 2021-02-06 12:54:47
问题 I'm writing a C++ program with OpenCV for lunar crater detection which seems to detect only a small fraction of craters accurately. My strategy for this approach was to first convert the image to HSV, then use inRange() to catch the colors in a range of values to produce a threshold, then Gaussian blur it and use HoughCircles() to detect the circles. One thing that I am not fully understanding is that when I give inRange() a low and high threshold around a color, it simply does not return

Using inRange() in OpenCV to detect colors in a range

由 元气小坏坏 提交于 2021-02-06 12:54:31
问题 I'm writing a C++ program with OpenCV for lunar crater detection which seems to detect only a small fraction of craters accurately. My strategy for this approach was to first convert the image to HSV, then use inRange() to catch the colors in a range of values to produce a threshold, then Gaussian blur it and use HoughCircles() to detect the circles. One thing that I am not fully understanding is that when I give inRange() a low and high threshold around a color, it simply does not return
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