Exemplo n.º 1
0
        /// <summary>
        /// Renders the deep draw image(s) depending on the Octave's installed.
        /// </summary>
        /// <param name="bmpInput">Specifies the input image.</param>
        /// <param name="nFocusLabel">Specifies a label to focus on (use this when running on classifying layers).</param>
        /// <param name="dfDetailPercentageToOutput">Optionally, specifies the amount of detail to apply to the original image when producing the final image (Default = 0.25 for 25%).</param>
        /// <param name="strOutputDir">Optionally, specifies the output directory wheren images are to be output.  When <i>null</i>, no images are output, but are instead set in each Octave.</param>
        /// <param name="bVisualizeEachStep">Optionally, specifies to create an image at each step of the process which can be useful when making a video of the evolution (default = <i>false</i>).</param>
        /// <param name="rgDirectInputs">Optionally, specifies the direct inputs used to set each output.  When not <i>null</i> the direct inputs are used instead of the <i>nFocusLabel</i> whereby the
        /// network outputs are set to the direct input values and the <i>nFocusLabel</i> is used to index the image and should therefore be unique for each set of direct inputs.
        /// By default, this value is set to <i>null</i>.
        /// </param>
        /// <returns>Upon completing the render, this method returns <i>true</i>, otherwise if cancelled it returns <i>false</i>.</returns>
        public bool Render(Bitmap bmpInput, int nFocusLabel = -1, double dfDetailPercentageToOutput = 0.25, string strOutputDir = null, bool bVisualizeEachStep = false, float[] rgDirectInputs = null)
        {
            if (rgDirectInputs != null && nFocusLabel < 0)
            {
                throw new Exception("The focus label must be set to a unique value >= 0 that corresponds to this specific direct input set.");
            }

            // get the input dimensions from net
            Blob <T> blobSrc = m_net.blob_by_name("data");

            int nW = blobSrc.width;
            int nH = blobSrc.height;

            m_log.WriteLine("Starting drawing...");
            blobSrc.Reshape(1, 3, nH, nW);    // resize the networks input.

            // Set the base data.
            if (strOutputDir != null)
            {
                bmpInput.Save(strOutputDir + "\\input_image.png");
            }

            Datum d = ImageData.GetImageData(bmpInput, 3, false, -1);

            m_blobBase.mutable_cpu_data = m_transformer.Transform(d);

            m_blobDetail.SetData(0.0);
            m_blobBlur.SetData(0);

            for (int i = 0; i < m_rgOctaves.Count; i++)
            {
                Octaves o = m_rgOctaves[i];
                // Select layer.
                string strLayer = o.LayerName;

                // Add changed details to the image.
                if (nFocusLabel < 0)
                {
                    m_cuda.add(blobSrc.count(), m_blobBase.gpu_data, m_blobDetail.gpu_data, blobSrc.mutable_gpu_data, o.PercentageOfPreviousOctaveDetailsToApply);
                }

                for (int j = 0; j < o.IterationN; j++)
                {
                    if (m_evtCancel.WaitOne(0))
                    {
                        return(false);
                    }

                    if (nFocusLabel >= 0)
                    {
                        blobSrc.CopyFrom(m_blobBase);
                    }

                    double dfSigma    = o.StartSigma + ((o.EndSigma - o.StartSigma) * j) / o.IterationN;
                    double dfStepSize = o.StartStepSize + ((o.EndStepSize - o.StartStepSize) * j) / o.IterationN;

                    make_step(strLayer, dfSigma, dfStepSize, nFocusLabel, rgDirectInputs);

                    if ((bVisualizeEachStep || (j == o.IterationN - 1 && o.Save)))
                    {
                        // Get the detail.
                        m_cuda.sub(m_blobDetail.count(), blobSrc.gpu_data, m_blobBase.gpu_data, m_blobDetail.mutable_gpu_data);

                        if (dfDetailPercentageToOutput < 1.0)
                        {
                            // reuse blob blur memory.
                            m_cuda.add(m_blobBlur.count(), m_blobBase.gpu_data, m_blobDetail.gpu_data, m_blobBlur.mutable_gpu_data, dfDetailPercentageToOutput);
                        }
                        else
                        {
                            m_blobBlur.CopyFrom(blobSrc);
                        }

                        Image bmp = getImage(m_blobBlur);

                        if (nFocusLabel < 0)
                        {
                            Bitmap bmp1 = AdjustContrast(bmp, 0.9f, 1.6f, 1.2f);
                            bmp.Dispose();
                            bmp = bmp1;
                        }

                        if (strOutputDir != null)
                        {
                            string strFile = strOutputDir + "\\" + o.UniqueName + "_" + j.ToString();
                            if (nFocusLabel >= 0)
                            {
                                if (rgDirectInputs != null)
                                {
                                    strFile += "_idx_" + nFocusLabel.ToString();
                                }
                                else
                                {
                                    strFile += "_class_" + nFocusLabel.ToString();
                                }
                            }

                            bmp.Save(strFile + ".png");
                        }

                        if (j == o.IterationN - 1)
                        {
                            o.Images.Add(nFocusLabel, bmp);
                        }
                        else
                        {
                            bmp.Dispose();
                        }
                    }

                    m_log.Progress = (double)j / (double)o.IterationN;
                    m_log.WriteLine("Focus Label: " + nFocusLabel.ToString() + "  Octave: '" + o.LayerName + "' - " + j.ToString() + " of " + o.IterationN.ToString() + " " + m_log.Progress.ToString("P"));

                    if (nFocusLabel >= 0)
                    {
                        m_blobBase.CopyFrom(blobSrc);
                    }
                }

                // Extract details produced on the current octave.
                if (nFocusLabel < 0)
                {
                    m_cuda.sub(m_blobDetail.count(), blobSrc.gpu_data, m_blobBase.gpu_data, m_blobDetail.mutable_gpu_data);
                }
            }

            m_log.WriteLine("Rendering completed!");
            return(true);
        }
Exemplo n.º 2
0
 /// <summary>
 /// Add a new Octaves to the collection of Octaves to run.
 /// </summary>
 /// <param name="octaves">Specifies the Octaves to add.</param>
 public void Add(Octaves octaves)
 {
     m_rgOctaves.Add(octaves);
 }