using System;
using System.Collections.Generic;
using System.Drawing;
using System.IO;
using System.Linq;
using CNTK;

namespace CNTKDemo
{
	class MainClass
	{
		private static void PrintOutput<T>(uint sampleSize, List<List<T>> outputBuffer)
		{
			Console.WriteLine("The number of sequences in the batch: " + outputBuffer.Count);
			int seqNo = 0;
			uint outputSampleSize = sampleSize;
			foreach (var seq in outputBuffer)
			{
				Console.WriteLine(String.Format("Sequence {0} contains {1} samples.", seqNo++, seq.Count / outputSampleSize));
				uint i = 0;
				uint sampleNo = 0;
				foreach (var element in seq)
				{
					if (i++ % outputSampleSize == 0)
					{
						Console.Write(String.Format("    sample {0}: ", sampleNo));
					}
					Console.Write(element);
					if (i % outputSampleSize == 0)
					{
						Console.WriteLine(".");
						sampleNo++;
					}
					else
					{
						Console.Write(",");
					}
				}
			}
		}

		public static void Main(string[] args)
		{
			Console.WriteLine("Hello World!");

			var device = DeviceDescriptor.CPUDevice;

			const string outputName = "Plus2060";
			var inputDataMap = new Dictionary<Variable, Value>();

			// Load the model.
			Function modelFunc = Function.LoadModel("z.model", device);

			// Get output variable based on name
			Variable outputVar = modelFunc.Outputs.Where(variable => string.Equals(variable.Name, outputName)).Single();

			// Get input variable. The model has only one single input.
			// The same way described above for output variable can be used here to get input variable by name.
			Variable inputVar = modelFunc.Arguments.Single();
			var outputDataMap = new Dictionary<Variable, Value>();
			Value inputVal, outputVal;
			List<List<float>> outputBuffer;

			// Get shape data for the input variable
			NDShape inputShape = inputVar.Shape;
			uint imageWidth = inputShape[0];
			uint imageHeight = inputShape[1];
			uint imageChannels = inputShape[2];
			uint imageSize = inputShape.TotalSize;

			Console.WriteLine("Evaluate single image");

			// Image preprocessing to match input requirements of the model.
			Bitmap bmp = new Bitmap(Bitmap.FromFile("00000.png"));
			var resized = bmp.Resize((int)imageWidth, (int)imageHeight, true);
			List<float> resizedCHW = resized.ParallelExtractCHW();

			// Create input data map
			inputVal = Value.CreateBatch(inputVar.Shape, resizedCHW, device);
			inputDataMap.Add(inputVar, inputVal);

			// Create ouput data map. Using null as Value to indicate using system allocated memory.
			// Alternatively, create a Value object and add it to the data map.
			outputDataMap.Add(outputVar, null);

			// Start evaluation on the device
			modelFunc.Evaluate(inputDataMap, outputDataMap, device);

			// Get evaluate result as dense output
			outputBuffer = new List<List<float>>();
			outputVal = outputDataMap[outputVar];
			outputVal.CopyVariableValueTo(outputVar, outputBuffer);

			PrintOutput(outputVar.Shape.TotalSize, outputBuffer);
		}
	}
}