218 lines
5.5 KiB
Text
218 lines
5.5 KiB
Text
{
|
|
"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
|
|
}
|