main_fpn

main_fpn.py

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+import sys
+import os
+import csv
+import numpy as np
+import cv2
+import math
+import pose_utils
+import os
+import myparse
+import renderer_fpn
+## To make tensorflow print less (this can be useful for debug though)
+#os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' 
+#import ctypes; 
+print '> loading getRts'
+import get_Rts as getRts
+######## TMP FOLDER #####################
+_tmpdir = './tmp/'#os.environ['TMPDIR'] + '/'
+print '> make dir'
+if not os.path.exists( _tmpdir):
+    os.makedirs( _tmpdir )
+#########################################
+##INPUT/OUTPUT
+input_file = str(sys.argv[1]) #'input.csv'
+outpu_proc = 'output_preproc.csv'
+output_pose_db =  './output_pose.lmdb'
+output_render = './output_render'
+#################################################
+print '> network'
+_alexNetSize = 227
+_factor = 0.25 #0.1
+
+# ***** please download the model in https://www.dropbox.com/s/r38psbq55y2yj4f/fpn_new_model.tar.gz?dl=0 ***** #
+model_folder = './fpn_new_model/'
+model_used = 'model_0_1.0_1.0_1e-07_1_16000.ckpt' #'model_0_1.0_1.0_1e-05_0_6000.ckpt'
+lr_rate_scalar = 1.0
+if_dropout = 0
+keep_rate = 1
+################################
+data_dict = myparse.parse_input(input_file)
+## Pre-processing the images 
+print '> preproc'
+pose_utils.preProcessImage( _tmpdir, data_dict, './',\
+                            _factor, _alexNetSize, outpu_proc )
+## Runnin FacePoseNet
+print '> run'
+## Running the pose estimation
+getRts.esimatePose( model_folder, outpu_proc, output_pose_db, model_used, lr_rate_scalar, if_dropout, keep_rate, use_gpu=False )
+
+
+renderer_fpn.render_fpn(outpu_proc, output_pose_db, output_render)