Orange Effect Camera Application – This article will show you how to take a camera preview frame and apply some effects. It also describes how to apply the same effect to the final captured photo using only Tizen’s native camera and the Image Util C API.
In the example shown we want to add a sepia effect to the camera preview and the final image. Sepia is an effect that makes the image look like an old monochrome photograph, tinted with brown tones.
Orange Effect Camera Application
The goal of our concept is that the user already sees in a preview of the camera as the final image.
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Before reading this article, we recommend that you familiarize yourself with the basic usage of the native camera API at the link below:
So you should be able to create your own basic camera app that provides a preview and takes a photo. You can also download and familiarize yourself with one of the SDK sample apps with camera functionality.
With the following instructions, you will be able to modify your application to provide a sepia effect on the preview and final images.
Since we already have a simple camera app working (either one of the sample Tizen camera apps or a DIY app), here’s a quick rundown of the steps we need to take to get things up and running:
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Figure 1: Image taken with a camera app without the sepia effect (left) and image taken with an app with the effect (right)
To separate the image manipulation code for easy reuse in the sample code, we put all the image manipulation functions into a pair of header and source files. Only three functions should be called “external” in the camera application code: prepare_camera(), modify_final_image(), and finalize_taking_picture(). They are listed in the img-mods.h header that you should include in your application.
The sepia effect is a toning effect that affects the image as a whole, turning it into a monochromatic image, colored with different shades of a single color: brown. That’s why the easiest way to apply it is to do it in the luminance-chrominance color space.
In Tizen, the video stream is encoded in NV12, which is an encoding consisting of luminance data and two chrominance components. It is a good format to apply the sepia effect directly because we don’t need additional conversion to separate the brightness and color information and modify it.
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Camera preview frames are given to us in NV12 by default, so we don’t need to configure the preview data encoding before starting the preview.
However, to make the final encoded image in NV12, we need to configure the camera capture in NV12:
Since these two functions can be called at the same time, we can wrap them in a convenient function:
… which we call in the camera app code just after we start the camera with camera_create() and before we start the preview with the camera_start_preview() API:
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In step 1, we registered a callback to execute on each frame of the camera view we received. Now we need to define this callback.
In the case of Samsung Z1 and Z3 devices, the pre-frame is encoded in 2 NV12 planes. What does it mean?
NV12 is a specific case of Y’CbCr color space image coding. You can read more about Y’CbCr on Wikipedia https://en.wikipedia.org/wiki/YCbCr. Y’CbCr is commonly called YUV (although it’s not exactly the same format as native YUV as you’d find on analog TV). Each pixel can be defined by the luma value (Y’), associated with the luminance, and the values of the chromatic components: Cb (usually called U) and Cr (usually called V), which determine the color of a pixel. . The NV12 uses so-called chromatic subsampling. As you can see in Figure 2, if the image is encoded in NV12, each pixel has its own unique luma value, but four neighboring pixels share a color value. Color is defined by a pair of chromatic components. It makes sense to reduce color data and reduce their resolution in favor of luminance data, because the human eye is not as sensitive to color as it is to light.
NV12 2-plane means that the frame data is stored in 2 planes: one is the Y plane which stores the luminance data information and the other is the UV plane which stores the chrominance data information.
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Calling the camera_preview_cb type gives us the pointer to the camera_preview_data_s structure that defines the camera view frame.
Since the sepia effect converts the image to the monochromatic color scale built into a brown color, it can easily be done in the luma and chroma planes separately. We can put our operations into two separate functions: one by multiplying the luma value to provide an old-style image overexposure effect, and the second by bringing the brown tone to the image, which in our case means replacing the values of chrome. components from constants. .
Old photos, especially amateur ones, are usually overexposed or underexposed. In this example we’ll use a simple trick to remove highlights to make a snapshot of an old photo.
We can easily do this by multiplying the luma value by a constant, in the example below, by 1.5.
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To avoid exceeding the range of values, we create a simple function below. In our example, we will not use the negative section clipping values (we will only increase the brightness).
Chroma modification is reduced to simply setting the Cb and Cr compounds at constant values, which determine the brown color (we chose Cb = 114, Cr = 144). As you have already seen in the figure shown earlier, even bytes in data.double_plane.uv mean Cr values, while even bytes mean Cb values.
Overall, we’ve packaged everything that needs to be done in this step into two convenient functions: modify_final_image() and finalize_taking_picture(). The first performs operations on the image itself. The latter saves the image as a file in a required path of a storage memory and updates the media database and will be explained in step 4.
The texture represented by the NV12 captured image is slightly different from the preview frame texture we saw earlier. The structure contains a data string containing Y and UV (CbCr) data under a pointer. However, the luma-to-chroma byte ratios are the same: each pixel contains a single luma value, and the chroma value pair is subsampled by groups of 4 pixels.
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That’s why, if we provide properly configured pointers as parameters, we can manipulate the luma and chroma data of the captured image, using the same functions we implemented for the frame preview modes: _luma_mod_blow_highlights() and _chroma_mod_sepia( ).
The last thing we need to do is encode the edited image to JPEG and save it to the device storage. This is done using the image_util_encode_jpeg() API function.
We could end here, but it might also be useful to immediately update the media database with the most recently taken photo. You don’t have to do this, but calling media_content_scan_file() will make the newly taken photo appear in apps like Gallery.
As you can see now, using Tizen’s native API and nothing else, you can get and edit the camera preview and a captured image. You can now edit any camera app using the tips presented in this article, as well as create your own more complex edits to the preview and/or camera images.
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