Hi,
I am very interested in your work and try to reproduce it
I notice these errors in sanity_test/code/train.py
print ("################TEST ON Rodriguez-vectors, input=r_matrix, loss=geodesic#####################")
model_rmg = Model(is_linear=False, out_rotation_mode="Rodriguez-vectors")
train(model_emg, input_mode = "r_matrix", loss_mode="geodesic", sampling_method="quaternion",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"rmg/")
model should be model_rmg
print ("################TEST ON euler_sin_cos, input=r_matrix, loss=geodesic#####################")
model_escmg = Model(is_linear=False, out_rotation_mode="euler_sin_cos")
train(model_emg, input_mode = "r_matrix", loss_mode="geodesic", sampling_method="axis_angle",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"escmg/")
model should be model_escmg
print ("################TEST ON Quaternion_half, input=r_matrix, loss=geodesic#####################")
model_qhmp = Model(is_linear=False, out_rotation_mode="Quaternion_half")
train(model_emg, input_mode = "r_matrix", loss_mode="pose", sampling_method="quaternion",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"qhmp/")
model_qhmg = Model(is_linear=False, out_rotation_mode="Quaternion_half")
train(model_emg, input_mode = "r_matrix", loss_mode="geodesic", sampling_method="quaternion",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"qhmg/")
model should be model_qhmg
I run train.py after these modifications
training with loss = pose
ran without problem
for all the cases with loss = geodesic after fzx iterations I got loss is NaN
please see issue with geodesic loss
Hi,
I am very interested in your work and try to reproduce it
I notice these errors in sanity_test/code/train.py
print ("################TEST ON Rodriguez-vectors, input=r_matrix, loss=geodesic#####################")
model_rmg = Model(is_linear=False, out_rotation_mode="Rodriguez-vectors")
train(model_emg, input_mode = "r_matrix", loss_mode="geodesic", sampling_method="quaternion",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"rmg/")
model should be model_rmg
print ("################TEST ON euler_sin_cos, input=r_matrix, loss=geodesic#####################")
model_escmg = Model(is_linear=False, out_rotation_mode="euler_sin_cos")
train(model_emg, input_mode = "r_matrix", loss_mode="geodesic", sampling_method="axis_angle",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"escmg/")
model should be model_escmg
print ("################TEST ON Quaternion_half, input=r_matrix, loss=geodesic#####################")
model_qhmp = Model(is_linear=False, out_rotation_mode="Quaternion_half")
train(model_emg, input_mode = "r_matrix", loss_mode="pose", sampling_method="quaternion",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"qhmp/")
model_qhmg = Model(is_linear=False, out_rotation_mode="Quaternion_half")
train(model_emg, input_mode = "r_matrix", loss_mode="geodesic", sampling_method="quaternion",batch=64 , total_iter=500001, out_weight_folder=out_weight_folder+"qhmg/")
model should be model_qhmg
I run train.py after these modifications
training with loss = pose
ran without problem
for all the cases with loss = geodesic after fzx iterations I got loss is NaN
please see issue with geodesic loss