Question

我需要读取图像像素颜色，图像将只有黑白两色。因此，如果像素是白色，我想实例化白色立方体，如果像素是黑色，我想实例化黑色立方体。现在这对我来说是全新的，所以我进行了一些挖掘，最后我使用了system.Drawing和bitmaps。但是现在我卡住了。我不知道如何检查白色像素

例如

private void Pixelreader()
{
    Bitmap img = new Bitmap(("ImageName.png");
    for (int i = 0; i < img.Width; i++)
    {
        for (int j = 0; j < img.Height; j++)
        {
            System.Drawing.Color pixel = img.GetPixel(i, j);

            if (pixel == *if image is white)
            {
               // instantiate white color.
            }
        }
    }
}

有没有其他方法可以做到这一点？谢谢！

Answer 1

如果图像只是真正的黑白（即所有像素都等于System.Drawing.Color.Black或System.Drawing.Color.White），那么您可以直接与这些颜色进行比较。在您发布的代码中，它将如下所示：

if (pixel == System.Drawing.Color.White)
{
    //instantiate white color.
}

如果图像是Unity资产的一部分，更好的方法是使用Resources读取它。将图像放入Assets / Resources文件夹;然后你可以使用以下代码：

Texture2D image = (Texture2D)Resources.Load("ImageName.png");

如果图像是全黑或全白，则无需循环 - 只需检查一个像素：

if(image.GetPixel(0,0) == Color.White)
{
    //Instantiate white cube
}
else
{
    //Instantiate black cube
}

Answer 2

您实际上可以将图像作为资源加载到Texture2D中，然后使用UnityEngine.Texture2D和UnityEngine.Color.GrayScale检查您获得的颜色是否足够接近白色。

Answer 3

听起来你有点过分使用它，而是可以使用已内置于Unity的功能。尝试在光线投射过程中查看像素颜色。

def getImage(filename):
    # convert filenames to a queue for an input pipeline.
    filenameQ = tf.train.string_input_producer([filename],num_epochs=None)

    # object to read records
    recordReader = tf.TFRecordReader()

    # read the full set of features for a single example 
    key, fullExample = recordReader.read(filenameQ)

    # parse the full example into its' component features.
    features = tf.parse_single_example(
        fullExample,
        features={
            'image/height': tf.FixedLenFeature([], tf.int64),
            'image/width': tf.FixedLenFeature([], tf.int64),
            'image/colorspace': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
            'image/channels':  tf.FixedLenFeature([], tf.int64),            
            'image/class/label': tf.FixedLenFeature([],tf.int64),
            'image/class/text': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
            'image/format': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
            'image/filename': tf.FixedLenFeature([], dtype=tf.string,default_value=''),
            'image/encoded': tf.FixedLenFeature([], dtype=tf.string, default_value='')
        })


    # now we are going to manipulate the label and image features

    label = features['image/class/label']
    image_buffer = features['image/encoded']

    # Decode the jpeg
    with tf.name_scope('decode_jpeg',[image_buffer], None):
        # decode
        image = tf.image.decode_jpeg(image_buffer, channels=3)

        # and convert to single precision data type
        image = tf.image.convert_image_dtype(image, dtype=tf.float32)


    # cast image into a single array, where each element corresponds to the greyscale
    # value of a single pixel. 
    # the "1-.." part inverts the image, so that the background is black.
    # re-define label as a "one-hot" vector 
    # it will be [0,1] or [1,0] here. 
    # This approach can easily be extended to more classes.
    image=tf.reshape(image,[height,width,3])
    label=tf.pack(tf.one_hot(label-1, nClass))

    return label, image


label, image = getImage("train-00000-of-00001")
imageBatch, labelBatch = tf.train.shuffle_batch(
    [image, label], batch_size=2,
    capacity=20,
    min_after_dequeue=10)

sess = tf.InteractiveSession()
sess.run(tf.initialize_all_variables())
# start the threads used for reading files
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess,coord=coord)
batch_xs, batch_ys = sess.run([imageBatch, labelBatch])
print batch_xs

coord.request_stop()
coord.join(threads)

Taken from here

Unity：读取图像像素颜色并基于

3 个答案: