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Diffstat (limited to 'fw/tools/MatrixTransform.ipynb')
| -rw-r--r-- | fw/tools/MatrixTransform.ipynb | 218 |
1 files changed, 218 insertions, 0 deletions
diff --git a/fw/tools/MatrixTransform.ipynb b/fw/tools/MatrixTransform.ipynb new file mode 100644 index 0000000..8e95469 --- /dev/null +++ b/fw/tools/MatrixTransform.ipynb @@ -0,0 +1,218 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 129, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import struct\n", + "\n", + "import serial\n", + "import PIL\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "import crc" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "digit_mask = PIL.Image.open('scans/digit.png')\n", + "seg_masks = [ np.asarray(PIL.Image.open('segmasks/seg{}.png'.format(i)), dtype=np.float)[:,:,0]/255.0 for i in range(1,9) ]\n", + "digit_h, digit_w = seg_masks[0].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "pic = PIL.Image.open('circle.jpg')" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "dpi = 600\n", + "scale = 1000/5091\n", + "stride_x, stride_y = 1.0*dpi*scale, 38.8/25.4*dpi*scale" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "mask_w, mask_h = int(8*stride_x)+1, int(4*stride_y)+1\n", + "resized = np.asarray(pic.resize((mask_w, mask_h), PIL.Image.BILINEAR).convert('HSV'), dtype=np.float)[:,:,2]/255" + ] + }, + { + "cell_type": "code", + "execution_count": 196, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def sub(resized, x, y):\n", + " return resized[int(y*stride_y):int(y*stride_y)+digit_h, int(x*stride_x):int(x*stride_x)+digit_w]" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def digit_values(resized, x, y):\n", + " img = sub(resized, x, y)/255.0\n", + " for mask in seg_masks:\n", + " yield np.average(np.multiply(mask, img))" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def make_vals(resized):\n", + " subvals = np.zeros((8, 4, 8), dtype=np.float)\n", + " for x in range(8):\n", + " for y in range(4):\n", + " subvals[x,y] = list(digit_values(resized, x, y))\n", + " return subvals" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def send_packet(ser, resized, addr=5):\n", + " gamma = 2\n", + " out = np.clip(np.power(make_vals(resized), 1/gamma)*255, 0, 255).astype(np.uint8)\n", + " pkt = b''\n", + " for x in range(8):\n", + " for y in range(4):\n", + " pkt += bytes(out[x,y,:]) + b'\\x00\\x00'\n", + " pkt += b'\\x03\\x00\\x00\\x00'\n", + " pkt += struct.pack('I', crc.crc(pkt))\n", + " pkt = bytes([0x40 | addr]) + pkt\n", + " ser.write(pkt)\n", + " return out" + ] + }, + { + "cell_type": "code", + "execution_count": 205, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 0],\n", + " [2, 3, 0, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [1, 2, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [3, 3, 3, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 2, 2, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [0, 2, 2, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [1, 0, 2, 0, 0, 0, 0, 0],\n", + " [0, 0, 0, 0, 0, 0, 0, 0],\n", + " [3, 3, 3, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 0, 3, 1, 1],\n", + " [2, 0, 3, 2, 1, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1]],\n", + "\n", + " [[3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1],\n", + " [3, 3, 3, 3, 3, 3, 3, 1]]], dtype=uint8)" + ] + }, + "execution_count": 205, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ser = serial.Serial('/dev/serial/by-id/usb-FTDI_FT232R_USB_UART_A90JRHXH-if00-port0', 2000000)\n", + "send_packet(ser, resized)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.5.3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} |