making repo pip compatiable

Author: ahmedosman

demo/compare_frameworks.py

@@ -20,7 +20,7 @@
 # Code Developed by:
 # Ahmed A. A. Osman
 
-from ch.star import STAR
+from star.ch.star import STAR
 import numpy as np
 batch_size = 1
 
@@ -33,7 +33,7 @@
 model.pose[:]  = np_pose[0]
 model.betas[:] = np_betas[0]
 
-from tf.star import STAR
+from star.tf.star import STAR
 import tensorflow as tf
 import numpy as np
 
@@ -45,7 +45,7 @@
 tf_star = star(pose,betas,trans)
 print(np.sqrt(np.sum((tf_star.numpy()-model.r)**2.0)))
 
-from pytorch.star import STAR
+from star.pytorch.star import STAR
 star = STAR(gender='female',num_betas=10)
 import torch
 import numpy as np

demo/load_chumpy.py

@@ -19,30 +19,18 @@
 # Code Developed by:
 # Ahmed A. A. Osman
 
-from STAR.ch.star import STAR
+from star.ch.star import STAR
 import numpy as np
 
 model = STAR(gender='female',num_betas=10)
 ## Assign random pose and shape parameters
 model.pose[:] = np.random.rand(model.pose.size) * .2
 model.betas[:] = np.random.rand(model.betas.size) * .03
 
-## Write to an .obj file
-outmesh_path = './hello_smpl.obj'
-with open( outmesh_path, 'w') as fp:
-    for v in model.r:
-        fp.write( 'v %f %f %f\n' % ( v[0], v[1], v[2]) )
-
-    for f in model.f+1: # Faces are 1-based, not 0-based in obj files
-        fp.write( 'f %d %d %d\n' %  (f[0], f[1], f[2]) )
-
-## Print message
-print ('..Output mesh saved to: {}'.format(outmesh_path))
-
 for j in range(0,10):
     model.betas[:] = 0.0  #Each loop all PC components are set to 0.
     for i in np.linspace(-3,3,10): #Varying the jth component +/- 3 standard deviations
         model.betas[j] = i
-        print(model.r) #vertices=model.r and faces=model.f
-        time.sleep(0.1)
+   
+
 

demo/load_tf.py

@@ -19,7 +19,7 @@
 # Code Developed by:
 # Ahmed A. A. Osman
 
-from tf.star import STAR
+from star.tf.star import STAR
 import tensorflow as tf
 import numpy as np
 batch_size = 10
@@ -28,4 +28,4 @@
 trans = tf.constant(np.zeros((1,3)),dtype=tf.float32)
 pose = tf.constant(np.zeros((1,72)),dtype=tf.float32)
 betas = tf.constant(np.zeros((1,10)),dtype=tf.float32)
-print(star(pose,betas,trans))
+print(star(pose,betas,trans))

demo/load_torch.py

@@ -18,7 +18,7 @@
 #
 # Code Developed by:
 # Ahmed A. A. Osman
-from STAR.pytorch.star import STAR
+from star.pytorch.star import STAR
 import numpy as np
 from numpy import newaxis
 import pickle
@@ -43,15 +43,3 @@
 shaped = model.v_shaped[-1, :, :]
 
 
-## Write to an .obj file
-outmesh_path = './hello_star_pytorch.obj'
-with open( outmesh_path, 'w') as fp:
-    for v in shaped:
-        fp.write( 'v %f %f %f\n' % ( v[0], v[1], v[2]) )
-
-    for f in model.f+1: # Faces are 1-based, not 0-based in obj files
-        fp.write( 'f %d %d %d\n' %  (f[0], f[1], f[2]) )
-
-## Print message
-print ('..Output mesh saved to: {}'.format(outmesh_path))
-       

demo/profile_tf.py

@@ -19,7 +19,7 @@
 # Code Developed by:
 # Ahmed A. A. Osman
 
-from tf.star import STAR 
+from star.tf.star import STAR 
 import tensorflow as tf 
 import time 
 import numpy as np 
@@ -35,4 +35,4 @@
         xstart = time.time()
         verts = star(pose,betas,trans)
         list_time.append(time.time()-xstart)
-    print('Batch Size %d, Duration %f'%(batch_size,np.mean(list_time[10:])))
+    print('Batch Size %d, Duration %f'%(batch_size,np.mean(list_time[10:])))

demo/profile_torch.py

@@ -20,7 +20,7 @@
 # Ahmed A. A. Osman
 
 
-from pytorch.star import STAR
+from star.pytorch.star import STAR
 import tensorflow as tf 
 import torch
 import numpy as np 

setup.py

@@ -26,7 +26,7 @@
 REQUIREMENTS = ["numpy", "chumpy", "opencv-python"]
 
 setuptools.setup(
-     name='STAR',  
+     name='star',  
      version='0.0.1',
      author="Ahmed A. A. Osman",
      author_email="ahmed.osman@tuebingen.mpg.de",