Readme authors

Author: alexfrostdesu

DeepLabStream.py

@@ -115,6 +115,7 @@ def __init__(self):
         self.frame_index = 0
         self._fps_counter = []
         self._fps = 0
+        self.greetings()
 
     @ staticmethod
     def set_camera_manager():
@@ -513,6 +514,11 @@ def create_dataframes(self):
     ######
     # meta
     ######
+    @staticmethod
+    def greetings():
+        print("This is DeepLabStream")
+        print("Developed by: Jens Schweihoff and Matvey Loshakov")
+
     def get_camera_manager(self):
         return self._camera_manager
 

Readme.md

@@ -127,3 +127,8 @@ killall -9 python
 ```
 
 ## License
+
+## Authors
+Lead Researcher: Jens Schweihoff, [email protected]
+
+Lead Developer: Matvey Loshakov, [email protected]

utils/configloader.py

@@ -44,3 +44,4 @@ def get_script_path():
 RECORD_EXP = dsc_config['Experiment'].getboolean('RECORD_EXP')
 
 START_TIME = time.time()
+EGG = "".join(format(ord(x), 'b') for x in "Hello there!")

utils/plotter.py

@@ -1,4 +1,6 @@
 import cv2
+import random
+from utils.configloader import EGG
 
 
 def plot_dots(image, coordinates, color, cond=False):
@@ -63,3 +65,8 @@ def plot_triggers_response(image, response):
             cv2.circle(image, **plot['circle'], thickness=2)
         if 'square' in plot:
             cv2.rectangle(image, **plot['square'], thickness=2)
+
+
+def plot_special_peak():
+    if random.randint(0, 100000) == 1:
+        print(EGG)

utils/poser.py

@@ -3,6 +3,7 @@
 import numpy as np
 from itertools import product, combinations
 from utils.analysis import calculate_distance
+from utils.plotter import plot_special_peak
 from skimage.feature import peak_local_max
 from scipy.ndimage.measurements import label, maximum_position
 from scipy.ndimage.morphology import generate_binary_structure, binary_erosion
@@ -67,6 +68,7 @@ def find_local_peaks_new(scoremap: np.ndarray, local_reference: np.ndarray, anim
 
     :returns all_joints dictionary with coordinates as list of tuples for each joint
     """
+
     # loading animal joints from config
     all_joints_names = config['all_joints_names']
     # critical_joints = ['neck', 'tailroot']
@@ -75,6 +77,7 @@ def find_local_peaks_new(scoremap: np.ndarray, local_reference: np.ndarray, anim
     stride = config['stride']
     # filtering scoremap
     scoremap[scoremap < 0.1] = 0
+    plot_special_peak()
     for joint_num, joint in enumerate(all_joints_names):
         all_peaks[joint] = []
         # selecting the joint in scoremap and locref