partial changes with model delpoyment

mushr_rhc_ros/launch/real/real_model_deploy_new.launch

@@ -10,12 +10,13 @@
     <arg name="n_layers" default="12" />
 
     <!-- action model -->
+    <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/6m_scratch/GPTcorl_6m_pre_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.1_weightdecay_0.0001_weightdecayb_0.1_lr_6e-4_2022-06-13_1655139613.6754146_2022-06-13_1655139613.6754277/model/epoch10.pth.tar" /> -->
     <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_3/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.1_weightdecay_0.0001_weightdecayb_0.1_lr_6e-4_2022-06-10_1654843603.5495381_2022-06-10_1654843603.5495553/model/epoch30.pth.tar" />
     <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_0/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_0_nla_6_nhe_8_statel_0.01_2022-06-03_1654253046.3212142_2022-06-03_1654253046.3212266/model/epoch30.pth.tar" /> -->
     <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_0/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_24_nhe_8_statel_0.01_2022-06-03_1654235683.085602_2022-06-03_1654235683.0856125/model/epoch30.pth.tar" /> -->
 
     <!-- map model -->
-    <arg name="use_map" default="true" />
+    <arg name="use_map" default="false" />
     <!-- without fine-tuning, 100% of data -->
     <arg name="model_path_map" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/finetune_episodes_map_4/GPTcorl_map_trainm_map_sta_pointnet_traini_1_nla_12_nhe_8_fre_False_2022-06-11_1654906825.070987_2022-06-11_1654906825.0709982/model/epoch20.pth.tar" />
 

mushr_rhc_ros/launch/sim/sim_server_eval.launch

@@ -10,7 +10,8 @@
     <arg name="n_layers" default="12" />
 
     <!-- action model -->
-    <arg name="model_path_act" type="str" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_3/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.1_weightdecay_0.0001_weightdecayb_0.1_lr_6e-4_2022-06-10_1654843603.5495381_2022-06-10_1654843603.5495553/model/epoch31.pth.tar" />
+    <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/6m_scratch/GPTcorl_6m_pre_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.1_weightdecay_0.0001_weightdecayb_0.1_lr_6e-4_2022-06-13_1655139613.6754146_2022-06-13_1655139613.6754277/model/epoch10.pth.tar" />
+    <!-- <arg name="model_path_act" type="str" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_3/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.1_weightdecay_0.0001_weightdecayb_0.1_lr_6e-4_2022-06-10_1654843603.5495381_2022-06-10_1654843603.5495553/model/epoch31.pth.tar" /> -->
 
     <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/hvd_test_16/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_1_nla_12_nhe_8_statel_0.01_2022-06-02_1654131996.2524076_2022-06-02_1654131996.2524228/model/epoch30.pth.tar" /> -->
     <!-- <arg name="model_path_act" default="/home/rb/hackathon_data_premium/aml_outputs/log_output/model_sizes_0/GPTcorl_scratch_trainm_e2e_statet_pointnet_traini_0_nla_6_nhe_8_statel_0.01_2022-06-03_1654253046.3212142_2022-06-03_1654253046.3212266/model/epoch30.pth.tar" /> -->
@@ -61,6 +62,8 @@
 
             <param name="car_name" value="$(arg car_name)" />
 
+            <param name="is_real_deployment" value="false" />
+
             <rosparam file="$(find mushr_rhc_ros)/launch/params/trajgen/$(arg tg).yaml" />
             <rosparam file="$(find mushr_rhc_ros)/launch/params/all_params.yaml" />
             <rosparam file="$(find mushr_rhc_ros)/launch/sim/params.yaml" />

mushr_rhc_ros/src/mingpt/model_resnetdirect.py

@@ -21,8 +21,7 @@
 
 import sys
 sys.path.append('../')
-from models.compass.select_backbone import select_resnet
-
+# from models.compass.select_backbone import select_resnet
 
 class ResnetDirect(nn.Module):
     """  the full GPT language model, with a context size of block_size """

mushr_rhc_ros/src/preprocessing_utils.py

@@ -13,7 +13,8 @@ def denorm_angle(angle):
     return (angle*(act_max-act_min)+act_max+act_min)/2
 
 def load_params(data_col):
-    condition = (data_col[1:]<12.0) & (data_col[1:]>0.5) & (~np.isnan(data_col[1:]))
+    condition = (data_col[1:]<12.0) & (data_col[1:]>0.5) & (~np.isnan(data_col[1:])) # params for the dataset collection
+    # condition = (data_col[1:]<4.0) & (data_col[1:]>0.1) & (~np.isnan(data_col[1:]))
     ok_R = np.extract(condition, data_col[1:])
     num_points = ok_R.shape[0]
     # angles = np.linspace(0, 2*np.pi, 720)*-1.0 + np.pi # aligned in car coordinate frame (because ydlidar points backwards)

mushr_rhc_ros/src/rhcnode_network_pcl_new.py

@@ -41,6 +41,8 @@
 import preprocessing_utils as pre
 from visualization_msgs.msg import Marker
 
+import cv2
+
 # import torch_tensorrt
 
 
@@ -695,6 +697,11 @@ def process_scan(self, msg):
         scan[0] = msg.header.stamp.to_sec()
         scan[1:] = msg.ranges
         original_points, sensor_origins, time_stamps, pc_range, voxel_size, lo_occupied, lo_free = pre.load_params(scan)
+
+        vis_mat, nx, ny = pre.compute_bev_image(original_points, sensor_origins, time_stamps, pc_range, voxel_size)
+        cv2.imshow('graycsale image',vis_mat)
+        cv2.waitKey(1)
+
         points_to_save = np.zeros(shape=(720,2))
         points_to_save[:original_points.shape[0],:] = original_points[:,:2]
         if original_points.shape[0]>0: