Merge branch 'adi' into master

CameraNetwork/controller.py

@@ -1396,7 +1396,7 @@ def preprocess_array(
             correct_radiometric=True,
             ignore_date_extrinsic=False
     ):
-        """Apply preprocessing to the raw array:
+        """Apply pre-processing to the raw array:
         dark_image subtraction, normalization, vignetting, HDR...
 
         Args:

CameraNetwork/utils.py

@@ -606,15 +606,19 @@ def f(angles, calculated_directions, measured_directions):
 
 def find_camera_orientation(calculated_directions, measured_directions):
     """
-    Find the rotation of the camera based on the coordinates of a celestail object
-    The input is two sets. The first is x,y image coordinates of the object (taken
-    from several images). The second set is the azimuth/altitude coordinates of the
-    celestial object (in Horizontal coordinate system).
-    The output is the rotation matrix of the camera. The rotation matrix is converts
-    between world coordinates to camera coordinates, where the world coordinates
-    are centered in camera, z is in the zenith and the x-axis points to the North.
-    The inner calibration of the camera is given as a function that converts
-    between the image coordinates and the camera coordinates.
+    Find the rotation of the camera based on the coordinates of a celestial object.
+
+    The input includes two sets:
+    1. `calculated_directions` - is x,y image coordinates of the object (taken from several images).
+    2. `measured_directions` - is the azimuth/altitude coordinates of the celestial object (in Horizontal coordinate system).
+
+    The output is the rotation matrix of the camera.
+    The rotation matrix, converts between world coordinates to camera coordinates,
+    where the world coordinates are centered in camera, z is in the zenith and the x-axis
+    points to the North.
+
+    The inner calibration of the camera is given as a function that
+    converts between the image coordinates and the camera coordinates.
 
     Args:
         calculated_directions (array like): The reference direction of the celestial

Image_pipeline.md

@@ -68,7 +68,7 @@ Which of the objects is being used in the final mask calculation of the image?
 
 3. ***TODO*** Find a way to calculate the ROI automatically based on the grid projection?  
 ### 2. Extrinsic calibration
-This proccess is done according to sun position and sunshader. 
+This process is done according to sun position and sunshader. 
 The process should apply for a sunny day having clear sky, and requires two steps:
 1. [handle_sunshader_scan()](https://github.com/Addalin/cameranetwork/blob/4f6a0b01111725799e6796dbf206f624a99c231b/CameraNetwork/server.py#L1066-L1088) 
 
@@ -106,6 +106,7 @@ Graphical Result:
 
 ![extrinsic](docs/source/images/snapshot_extrinsic.png)
 
+- See a mathematical description, see p.49-50 in Amit's thesis, section: "Self-Calibration in a Camera Network".
 
 ### 3. Radiometric calibration:
 To perform radiometric calibration with a sunphotometer, 
@@ -144,11 +145,13 @@ For example:
 
 ### 4. 3D grid and space curving:
 The [geographic coordinate systems](https://en.wikipedia.org/wiki/Geographic_coordinate_system) that are used here are: 
-1. The ECEF (earth-centered, earth-fixed frame) is the common 3D grid that is being used for moving the point-of-view (the observing camera) around the grid conveniently according to cameras' locations. 
+1. The ECEF (earth-centered, earth-fixed frame) is the common 3D grid that is being used for moving the point-of-view (the observing camera) around the grid conveniently according to cameras' location (Latitude (\phi), longitude (\lambda),X_ecef,Y_ecef,Z_ecef). 
 2. The NED (North East Down) grid (X,Y,Z) is used for visualization and reconstruction grid.
 
 See their definitions in the project [here](https://github.com/Addalin/cameranetwork/blob/c69dda2adc041dc2dc98660b34e57769213f23a9/CameraNetwork/gui/main.py#L1393-L1420). 
-
+image of the relation between both coordinates systems: https://en.wikipedia.org/wiki/Geographic_coordinate_system#/media/File:ECEF_ENU_Longitude_Latitude_relationships.svg
+// TODO : add the image to here.
+
 There are several conversion processes that are being done: 
 
 1. [ProjectGrid()](https://github.com/Addalin/cameranetwork/blob/fa7d2b2f29d5217cdc2b216ae55d147393e9db0d/CameraNetwork/image_utils.py#L615-L645) - Projecting the 3D grid of the interest volume, onto image plane. Which uses ecef2ned in [projectECEF()](https://github.com/Addalin/cameranetwork/blob/c69dda2adc041dc2dc98660b34e57769213f23a9/CameraNetwork/gui/main.py#L881-L933).