From 43416c4717d2430c3e11f042294d12b781fee2e1 Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期三, 27 九月 2017 04:09:30 +0800
Subject: [PATCH] Failed lstm experiment
---
practice/smoothing_ypr.ipynb | 83 ++++++++++++++++++++++-------------------
1 files changed, 45 insertions(+), 38 deletions(-)
diff --git a/practice/smoothing_ypr.ipynb b/practice/smoothing_ypr.ipynb
index a411c30..408f91e 100644
--- a/practice/smoothing_ypr.ipynb
+++ b/practice/smoothing_ypr.ipynb
@@ -2,10 +2,8 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 156,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 1,
+ "metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
@@ -17,31 +15,27 @@
},
{
"cell_type": "code",
- "execution_count": 157,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 3,
+ "metadata": {},
"outputs": [],
"source": [
"video_path = '../data/video/SGT036_2016_07_25_pivothead_AVI.avi'\n",
"bbox_path = '../data/video/annotations/SGT036_childface.txt'\n",
"\n",
- "annot_path = '../output/video/output-SGT036_resnet18_cr_epoch_1.txt'\n",
- "output_string = 'SGT036_resnet18_cr_epoch_1_flat_smoothed'"
+ "annot_path = '../output/video/output-SGT036_set4_normal_a1_epoch_25.txt'\n",
+ "output_string = 'SGT036_set4_normal_a1_epoch_25_smooth'"
]
},
{
"cell_type": "code",
- "execution_count": 158,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 4,
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[-6.069214 -0.831665 0.53318 ..., -3.836042 -3.868275 -2.377155]\n",
+ "[ 2.843239 6.065323 6.614468 ..., -0.936905 -1.396786 -3.20248 ]\n",
"(8508,)\n",
"(53464,)\n"
]
@@ -93,10 +87,8 @@
},
{
"cell_type": "code",
- "execution_count": 159,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 5,
+ "metadata": {},
"outputs": [
{
"name": "stdout",
@@ -107,31 +99,39 @@
}
],
"source": [
- "window_len = 6\n",
+ "window_len = 3\n",
"pad = window_len / 2\n",
"window = 'flat'\n",
+ "window_2 = 'flat'\n",
+ "window_len_2 = 7\n",
+ "pad_2 = window_len_2 / 2\n",
"\n",
"s = np.r_[y[window_len-1:0:-1],y,y[-2:-window_len-1:-1]]\n",
"t = np.r_[p[window_len-1:0:-1],p,p[-2:-window_len-1:-1]]\n",
"u = np.r_[r[window_len-1:0:-1],r,r[-2:-window_len-1:-1]]\n",
"\n",
- "xa = np.r_[x_min_arr[window_len-1:0:-1],x_min_arr,x_min_arr[-2:-window_len-1:-1]]\n",
- "xb = np.r_[x_max_arr[window_len-1:0:-1],x_max_arr,x_max_arr[-2:-window_len-1:-1]]\n",
- "ya = np.r_[y_min_arr[window_len-1:0:-1],y_min_arr,y_min_arr[-2:-window_len-1:-1]]\n",
- "yb = np.r_[y_max_arr[window_len-1:0:-1],y_max_arr,y_max_arr[-2:-window_len-1:-1]]\n",
+ "xa = np.r_[x_min_arr[window_len_2-1:0:-1],x_min_arr,x_min_arr[-2:-window_len_2-1:-1]]\n",
+ "xb = np.r_[x_max_arr[window_len_2-1:0:-1],x_max_arr,x_max_arr[-2:-window_len_2-1:-1]]\n",
+ "ya = np.r_[y_min_arr[window_len_2-1:0:-1],y_min_arr,y_min_arr[-2:-window_len_2-1:-1]]\n",
+ "yb = np.r_[y_max_arr[window_len_2-1:0:-1],y_max_arr,y_max_arr[-2:-window_len_2-1:-1]]\n",
"\n",
"if window == 'flat':\n",
" w=np.ones(window_len, 'd')\n",
"else:\n",
" w=eval('np.' + window + '(window_len)')\n",
+ " \n",
+ "if window_2 == 'flat':\n",
+ " w_2=np.ones(window_len_2, 'd')\n",
+ "else:\n",
+ " w_2=eval('np.' + window_2 + '(window_len_2)') \n",
"\n",
"y = np.convolve(w / w.sum(), s, mode='valid')[pad:-pad]\n",
"p = np.convolve(w / w.sum(), t, mode='valid')[pad:-pad]\n",
"r = np.convolve(w / w.sum(), u, mode='valid')[pad:-pad]\n",
- "x_min_arr = np.convolve(w / w.sum(), xa, mode='valid')[pad:-pad]\n",
- "x_max_arr = np.convolve(w / w.sum(), xb, mode='valid')[pad:-pad]\n",
- "y_min_arr = np.convolve(w / w.sum(), ya, mode='valid')[pad:-pad]\n",
- "y_max_arr = np.convolve(w / w.sum(), yb, mode='valid')[pad:-pad]\n",
+ "x_min_arr = np.convolve(w_2 / w_2.sum(), xa, mode='valid')[pad_2:-pad_2]\n",
+ "x_max_arr = np.convolve(w_2 / w_2.sum(), xb, mode='valid')[pad_2:-pad_2]\n",
+ "y_min_arr = np.convolve(w_2 / w_2.sum(), ya, mode='valid')[pad_2:-pad_2]\n",
+ "y_max_arr = np.convolve(w_2 / w_2.sum(), yb, mode='valid')[pad_2:-pad_2]\n",
"\n",
"pose_dict = {}\n",
"bbox_dict = {}\n",
@@ -151,10 +151,8 @@
},
{
"cell_type": "code",
- "execution_count": 160,
- "metadata": {
- "collapsed": false
- },
+ "execution_count": 7,
+ "metadata": {},
"outputs": [
{
"name": "stdout",
@@ -166,11 +164,20 @@
],
"source": [
"video = cv2.VideoCapture(video_path)\n",
- "width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH)) # float\n",
- "height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)) # float\n",
+ "# New cv2\n",
+ "# width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH)) # float\n",
+ "# height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)) # float\n",
+ "#\n",
+ "# # Define the codec and create VideoWriter object\n",
+ "# fourcc = cv2.VideoWriter_fourcc(*'MJPG')\n",
+ "# out = cv2.VideoWriter('output/video/output-%s.avi' % args.output_string, fourcc, 30.0, (width, height))\n",
+ "\n",
+ "# Old cv2\n",
+ "width = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)) # float\n",
+ "height = int(video.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)) # float\n",
"\n",
"# Define the codec and create VideoWriter object\n",
- "fourcc = cv2.VideoWriter_fourcc(*'MJPG')\n",
+ "fourcc = cv2.cv.CV_FOURCC(*'MJPG')\n",
"out = cv2.VideoWriter('../output/video/output-%s.avi' % output_string, fourcc, 30.0, (width, height))\n",
"\n",
"txt_out = open('../output/video/output-%s.txt' % output_string, 'w')\n",
@@ -226,9 +233,9 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
- "display_name": "Python [conda root]",
+ "display_name": "Python 2",
"language": "python",
- "name": "conda-root-py"
+ "name": "python2"
},
"language_info": {
"codemirror_mode": {
@@ -240,7 +247,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
- "version": "2.7.12"
+ "version": "2.7.13"
}
},
"nbformat": 4,
--
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