init - 初始化项目

doc/tutorials/imgproc/threshold_inRange/threshold_inRange.markdown

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+Thresholding Operations using inRange {#tutorial_threshold_inRange}
+=====================================
+
+@tableofcontents
+
+@prev_tutorial{tutorial_threshold}
+@next_tutorial{tutorial_filter_2d}
+
+|    |    |
+| -: | :- |
+| Original author | Lorena García |
+| Compatibility | Rishiraj Surti |
+
+Goal
+----
+
+In this tutorial you will learn how to:
+
+-   Perform basic thresholding operations using OpenCV @ref cv::inRange function.
+-   Detect an object based on the range of pixel values in the HSV colorspace.
+
+Theory
+------
+-   In the previous tutorial, we learnt how to perform thresholding using @ref cv::threshold function.
+-   In this tutorial, we will learn how to do it using @ref cv::inRange function.
+-   The concept remains the same, but now we add a range of pixel values we need.
+
+HSV colorspace
+--------------
+
+<a href="https://en.wikipedia.org/wiki/HSL_and_HSV">HSV</a> (hue, saturation, value) colorspace
+is a model to represent the colorspace similar to the RGB color model. Since the hue channel
+models the color type, it is very useful in image processing tasks that need to segment objects
+based on its color. Variation of the saturation goes from unsaturated to represent shades of gray and
+fully saturated (no white component). Value channel describes the brightness or the intensity of the
+color. Next image shows the HSV cylinder.
+
+![By SharkDderivative work: SharkD [CC BY-SA 3.0 or GFDL], via Wikimedia Commons](images/Threshold_inRange_HSV_colorspace.jpg)
+
+Since colors in the RGB colorspace are coded using the three channels, it is more difficult to segment
+an object in the image based on its color.
+
+![By SharkD [GFDL or CC BY-SA 4.0], from Wikimedia Commons](images/Threshold_inRange_RGB_colorspace.jpg)
+
+Formulas used to convert from one colorspace to another colorspace using @ref cv::cvtColor function
+are described in @ref imgproc_color_conversions
+
+Code
+----
+
+@add_toggle_cpp
+The tutorial code's is shown lines below. You can also download it from
+[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp)
+@include samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp
+@end_toggle
+
+@add_toggle_java
+The tutorial code's is shown lines below. You can also download it from
+[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java)
+@include samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java
+@end_toggle
+
+@add_toggle_python
+The tutorial code's is shown lines below. You can also download it from
+[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py)
+@include samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py
+@end_toggle
+
+Explanation
+-----------
+
+Let's check the general structure of the program:
+-   Capture the video stream from default or supplied capturing device.
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp cap
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java cap
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py cap
+    @end_toggle
+
+-   Create a window to display the default frame and the threshold frame.
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp window
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java window
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py window
+    @end_toggle
+
+-   Create the trackbars to set the range of HSV values
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp trackbar
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java trackbar
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py trackbar
+    @end_toggle
+
+-   Until the user want the program to exit do the following
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp while
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java while
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py while
+    @end_toggle
+
+-   Show the images
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp show
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java show
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py show
+    @end_toggle
+
+-   For a trackbar which controls the lower range, say for example hue value:
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp low
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java low
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py low
+    @end_toggle
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp low
+
+-   For a trackbar which controls the upper range, say for example hue value:
+
+    @add_toggle_cpp
+    @snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp high
+    @end_toggle
+
+    @add_toggle_java
+    @snippet samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java high
+    @end_toggle
+
+    @add_toggle_python
+    @snippet samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py high
+    @end_toggle
+
+-   It is necessary to find the maximum and minimum value to avoid discrepancies such as
+    the high value of threshold becoming less than the low value.
+
+Results
+-------
+
+-  After compiling this program, run it. The program will open two windows
+
+-  As you set the range values from the trackbar, the resulting frame will be visible in the other window.
+
+    ![](images/Threshold_inRange_Tutorial_Result_input.jpeg)
+    ![](images/Threshold_inRange_Tutorial_Result_output.jpeg)