Add automatic HSV tuner

.gitignore

@@ -2,4 +2,5 @@
 **/build
 **/install
 **/log
-**/__pycache__
+**/__pycache__
\ No newline at end of file
+**/hsv_params
\ No newline at end of file

README.md

@@ -65,6 +65,22 @@ export ROS_AUTOMATIC_DISCOVERY_RANGE=SUBNET #Tell ROS to make your nodes only ac
 1. Clone this repository : `git clone http://gvipers.imt-nord-europe.fr/ines.el.hadri/larm.git`
 
 
+### Tune the camera HSV
+
+First, put a bottle in front of the robot.
+
+Then, go in the `larm` directory and launch the HSV tuner python script using the following command
+```
+python3 src/config/mask_tuner.py
+```
+
+A window will popup with a frame from the RealSense camera :
+- Make a rectangle selection of the inside of the bottle (every pixel in the rectangle should be green, make the biggest rectangle possible to have a lot of diversity in the green colors).
+- Then press enter to save the selection and calculate the HSV thresholds
+- If the mask seems good enough, press a key. Otherwise, press a key and restart the script
+
+> Every time you run the tuner script, you will have to rebuild the package (see [Build the package](#build-the-packages))
+
 ### Build the packages
 In the same ROS2 workspace directory:
 - `./master/bin/install`

grp_astro/CMakeLists.txt

@@ -42,6 +42,11 @@ install(DIRECTORY
   src/img
   DESTINATION lib/${PROJECT_NAME}
 )
+# Copy HSV tuning
+install(DIRECTORY
+  src/config
+  DESTINATION lib/${PROJECT_NAME}
+)
 
 # Python scripts
 install( PROGRAMS 

grp_astro/src/cam_vision

@@ -9,7 +9,6 @@ import cv2, pathlib, statistics
 from cv_bridge import CvBridge
 from cam_driver import CameraDriver
 import pyrealsense2 as rs
-import math
 
 
 
@@ -19,11 +18,30 @@ class CameraVision(CameraDriver):
     def __init__(self, name="cam_vision", timerFreq = 1/60.0):
         super().__init__(name, timerFreq) # Create the node
 
-        # Initialize node variables
-        self._low = np.array([60-25, 50, 50])
-        self._high = np.array([65+25, 255, 255])
-        self._kernel = np.ones((5, 5), np.uint8)
+        # Load parameters
+        directory = pathlib.PurePath(__file__).parent
+        try:
+            # Load HSV threshold params from file
+            file = open(str(directory / "config" / "hsv_params" ), "r")
+
+            # Parse string
+            text = file.read()
+            low = text.split(",")[0].strip('][ ')
+            high = text.split(",")[1].strip('][ ')
+
+            self._low = np.array([int(i) for i in low.split(" ") if i])
+            self._high = np.array([int(i) for i in high.split(" ") if i])
 
+            print(f"Successfully loaded HSV params :\n - low : {self._low}\n - high {self._high}")
+        except:
+            # Initialize default variables if no file exists
+            self._low = np.array([60-25, 50, 50])
+            self._high = np.array([65+25, 255, 255])
+
+            print("Set HSV params to default values :\n - low : {self._low}\n - high {self._high}")
+        
+        # Node variables
+        self._kernel = np.ones((5, 5), np.uint8)
         self._color_info = (0, 0, 255)
 
         # Initialize a ROS2 Image to CV2 image converter

grp_astro/src/config/mask_tuner.py

+#!/usr/bin/env python3
+## Doc: https://dev.intelrealsense.com/docs/python2
+
+###############################################
+##      Open CV and Numpy integration        ##
+###############################################
+
+import pyrealsense2 as rs
+import signal, time, numpy as np
+import sys, cv2
+import time
+
+# Configure depth and color streams
+pipeline = rs.pipeline()
+config = rs.config()
+
+# Get device product line for setting a supporting resolution
+pipeline_wrapper = rs.pipeline_wrapper(pipeline)
+pipeline_profile = config.resolve(pipeline_wrapper)
+device = pipeline_profile.get_device()
+device_product_line = str(device.get_info(rs.camera_info.product_line))
+
+print( f"Connect: {device_product_line}" )
+found_rgb = True
+for s in device.sensors:
+    print( "Name:" + s.get_info(rs.camera_info.name) )
+    if s.get_info(rs.camera_info.name) == 'RGB Camera':
+        found_rgb = True
+
+if not (found_rgb):
+    print("Depth camera required !!!")
+    exit(0)
+
+config.enable_stream(rs.stream.color, width=848, height=480, format=rs.format.bgr8, framerate=60)
+config.enable_stream(rs.stream.depth, width=848, height=480, format=rs.format.z16, framerate=60)
+
+# Capture ctrl-c event
+isOk= True
+def signalInterruption(signum, frame):
+    global isOk
+    print( "\nCtrl-c pressed" )
+    isOk= False
+
+signal.signal(signal.SIGINT, signalInterruption)
+
+# Start streaming
+pipeline.start(config)
+
+# VARIABLES
+low = np.array([179, 255, 255]) # Set to max so detected values will be inferior
+high = np.array([0, 0, 0]) #Set to min so detected values will be superior
+kernel = np.ones((5, 5), np.uint8)
+
+
+# Skip the first frames of the camera (for some reason they don't work well)
+for i in range(20):
+    frames = pipeline.wait_for_frames()
+    color_frame = frames.get_color_frame()
+
+
+if color_frame is not None:
+    exit
+
+# Convert image to numpy arrays
+color_image = np.asanyarray(color_frame.get_data())
+
+
+# Convert image to HSV for easier thresholding
+hsv_image = cv2.cvtColor(color_image, cv2.COLOR_BGR2HSV)
+
+
+# Define bottle area by mouse
+r = cv2.selectROI('Select region', color_image)
+selectedRegion = hsv_image[int(r[1]):int(r[1]+r[3]), int(r[0]):int(r[0]+r[2])]
+cv2.destroyWindow('Select region')
+
+# Calculate new HSV mask
+H = selectedRegion[:,:,0].flatten()
+S = selectedRegion[:,:,1].flatten()
+V = selectedRegion[:,:,2].flatten()
+hMargin = 15
+sMargin = 20
+vMargin = 20
+
+low = np.array([min(H) - hMargin, min(S) - sMargin, min(V) - vMargin])
+high = np.array([max(H) + hMargin, max(S) + sMargin, max(V) + vMargin])
+print("-> Low and high HSV saved in 'hsv_params' file :",low, high)
+
+# Vision
+# Seuillage par colorimétrie
+mask = cv2.inRange(hsv_image, low, high)
+
+# Réduction du bruit
+mask = cv2.erode(mask, kernel, iterations=4)
+mask = cv2.dilate(mask, kernel, iterations=4)
+
+mask_rgb = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
+
+# Show images
+images = np.hstack((color_image, mask_rgb))
+
+# Show images
+cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
+cv2.imshow('RealSense', images)
+cv2.waitKey(0)
+
+# Save values in a file
+file = open("hsv_params", "w")
+file.write(str(low) + "," + str(high))
+file.close()
+# Stop streaming
+print("\nEnding...")
+pipeline.stop()
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