Merge branch 'remote' into dev

config/prototype_of3.json

@@ -6,7 +6,8 @@
     "fps": 30,
     "units": 15,
     "units_used": 9, 
-    "resolution_stitch": [400, 400]
+    "resolution_stitch": [128, 128],
+    "stitch_res_list": [384,256,128,64]
   },
   "stitcher": {
     "min_area_frac": 0.01,

config/prototype_raft.json

@@ -0,0 +1,42 @@
+{
+  "name": "prototype",
+  "version": "1.0",
+  "camera": {
+    "resolution_raw": [1920, 1080],
+    "fps": 30,
+    "units": 15,
+    "units_used": 9, 
+    "resolution_stitch": [128, 128]
+  },
+  "stitcher": {
+    "min_area_frac": 0.01,
+    "max_area_frac": 0.04,
+    "max_aspect_ratio": 100,
+    "index": [1,2,3,6,7,8,11,12,13],
+    "margin": 10,
+    "nominal_ov_pos": 100,
+    "n": [3,3],
+    "row_tol": 0.6,
+    "box_size": [250, 250]
+  },
+  "tracker": {
+    "adaptive": true,
+    "lower_threshold": 12.0,
+    "upper_threshold": 18.0,
+    "loop_closure_interval": 1,
+    "algorithm": "raft",
+    "dis_preset": "medium",
+    "dis_mode": 3,
+    "algorithm_list": ["raft", "dis"]
+  },
+  "contact": {
+    "min_contour_area": 3000,
+    "flow_threshold":1,
+    "div_threshold":0.02,
+    "expansion_threshold": 0.01,
+    "kernel_size": [5,5],
+    "denoise_sigma": 15
+  }
+}
+
+

patch_generation/patch_generation_3_org.py

@@ -115,9 +115,9 @@ def generate_color_pattern(h, w, d, r):
 def main():
     # Parameters for the pattern.
     # For example, using 100x100 pixels image with patches of 3x3 pixels.
-    height = 1000
-    width = 1000
-    patch_size = 20
+    height = 2750
+    width = 1950
+    patch_size = 12
     # Set r to a value that gives sufficient difference.
     # Note: r is the threshold for squared difference per channel, and the condition is
     # |c - c_neighbor| >= sqrt(r). Very high r may make it impossible to satisfy.

src/orisys/tracker.py

@@ -1,9 +1,9 @@
 import cv2
 import numpy as np
+import time
 import torch
 import torchvision.transforms as T
-from torchvision.models.optical_flow import raft_large, raft_small
-import time
+from torchvision.models.optical_flow import raft_large
 
 class Tracker:
     def __init__(self,