diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/0.5_detect.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/0.5_detect.jpg
index 3b2f09ab135d9b1029dc1fb1a6fdbe3e40c5a5f9..5be80f575311b7c6a9a2b3d4e6fcda4b290fd54e 100644
Binary files a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/0.5_detect.jpg and b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/0.5_detect.jpg differ
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/out.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/out.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..3b2f09ab135d9b1029dc1fb1a6fdbe3e40c5a5f9
Binary files /dev/null and b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/Calibration_cam/out.jpg differ
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/MCL.py b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/MCL.py
index ee5961f9bd32efd43fdd74c993594a22eef03cbb..9662f29d2c6c849d9370bceb6ac7d00c0b5b527e 100644
--- a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/MCL.py
+++ b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/MCL.py
@@ -4,7 +4,9 @@
#import tensorflow as tf
#from yolov3.utils import detect_image, detect_realtime, detect_video, Load_Yolo_model, detect_video_realtime_mp
#from yolov3.configs import *
-#import matplotlib.pyplot as plt
+import matplotlib.pyplot as plt
+#from mpl_toolkits.mplot3d import axes3d
+#from matplotlib import cm
import numpy as np
import random as rd
@@ -26,8 +28,8 @@ coord_ext = [(i/diametre , j/diametre) for i,j in zip(pixel_x_ext, pixel_y_ext)]
coord_int = [(i/diametre , j/diametre) for i,j in zip(pixel_x_int, pixel_y_int)]
### Paramètres ###
-sigma_position = 0.1
-sigma_direction = 30*3.1415/180
+sigma_position = 0.02
+sigma_direction = 15*3.1415/180
seuil_cone = 0.6
@@ -35,9 +37,9 @@ dep_x, dep_y, dep_theta = 1.314, 1.162, 3.14/3.6
nb_particule = 30
pos = [[dep_x, dep_y, dep_theta] for i in range(nb_particule)]
-F = 3951 #Focale camera
-h_reel = 0.24 #Hauteur d'un plot
-y_0 = 2000 #Milieu de l'image
+F = 3951/3 #Focale camera
+h_reel = 0.27 #Hauteur d'un plot
+y_0 = 1500 #Milieu de l'image
dist_roue = 0.25 #Distance entre les roues avant et les roues arrieres
@@ -136,6 +138,7 @@ def sensor_update(observation, position):
vision_x.append((pt[0]-x)*cos(theta) + (pt[1]-y)*sin(theta))
vision_y.append(-(pt[0]-x)*sin(theta) + (pt[1]-y)*cos(theta))
+
for pt in coord_ext:
vision_x_ext.append((pt[0]-x)*cos(theta) + (pt[1]-y)*sin(theta))
vision_y_ext.append(-(pt[0]-x)*sin(theta) + (pt[1]-y)*cos(theta))
@@ -143,22 +146,25 @@ def sensor_update(observation, position):
cones_vu_x = []
cones_vu_y = []
for i in range(len(vision_x)):
- if vision_x[i]>0 and abs(vision_y[i])<vision_x[i]:
+ if vision_x[i]>0 and abs(vision_y[i])<0.67*vision_x[i]:
cones_vu_x.append(vision_x[i])
cones_vu_y.append(vision_y[i])
for i in range(len(vision_x_ext)):
- if vision_x_ext[i]>0 and abs(vision_y_ext[i])<vision_x_ext[i]:
+ if vision_x_ext[i]>0 and abs(vision_y_ext[i])<0.67*vision_x_ext[i]:
cones_vu_x.append(vision_x_ext[i])
cones_vu_y.append(vision_y_ext[i])
-
- obs_x = []
- obs_y = []
- for i in observation:
- obs_x.append(i[0])
- obs_y.append(i[1])
-
- return 1/distance_Chamfer(cones_vu_x, cones_vu_y, obs_x, obs_y)
+
+ if len(cones_vu_x) == 0:
+ return 0
+ else:
+ obs_x = []
+ obs_y = []
+ for i in observation:
+ obs_x.append(i[0])
+ obs_y.append(i[1])
+
+ return 1/distance_Chamfer(cones_vu_x, cones_vu_y, obs_x, obs_y)**4
@@ -234,7 +240,106 @@ def get_position(boxes,commande,pos):
return pos_calc, pos, cone_x, cone_y
+if __name__ == "__main__":
+ # detection = [[2.18939087e+03, 1.48177417e+03, 2.86449023e+03, 2.54427783e+03, 9.66490030e-01, 0.00000000e+00],
+ # [4.22634644e+02, 1.44312561e+03, 1.08822302e+03, 2.31131567e+03, 9.36378121e-01, 0.00000000e+00],
+ # [1.33116504e+03, 1.42764783e+03, 1.70783643e+03, 1.98202075e+03, 9.03878212e-01, 0.00000000e+00],
+ # [2.11831836e+03, 1.41914294e+03, 2.43602563e+03, 1.87002930e+03, 9.03337121e-01, 0.00000000e+00],
+ # [2.24867358e+03, 1.59305701e+03, 2.99900000e+03, 3.76038647e+03, 8.82729828e-01, 0.00000000e+00],
+ # [2.64460254e+03, 1.44378406e+03, 2.91649780e+03, 2.14795459e+03, 3.62023830e-01, 0.00000000e+00]]
+
+ # detection = [[0.00000000e+00, 1.85167456e+03, 9.15495361e+02, 3.25824146e+03, 9.37295914e-01, 0.00000000e+00],
+ # [2.41986987e+03, 1.86332446e+03, 2.86713550e+03, 2.42170972e+03, 9.23870742e-01, 0.00000000e+00],
+ # [1.36284387e+03, 1.83517468e+03, 1.92408057e+03, 2.59739648e+03, 9.17667687e-01, 0.00000000e+00]]
+
+ detection = [[1.28486133e+03, 1.79538904e+03, 1.78743445e+03, 2.45994067e+03, 9.39055085e-01, 0.00000000e+00],
+ [0.00000000e+00, 1.87250220e+03, 7.69682068e+02, 3.12636377e+03, 9.35593545e-01, 0.00000000e+00],
+ [2.12719995e+03, 1.72824695e+03, 2.48698218e+03, 2.24433813e+03, 9.07173812e-01, 0.00000000e+00],
+ [2.72219897e+03, 2.18795605e+03, 2.99900000e+03, 3.47306348e+03, 3.55658233e-01, 0.00000000e+00]]
+
+ # detection = [[1.12150806e+03, 1.82397412e+03, 1.71230017e+03, 2.59400610e+03, 9.47640836e-01, 0.00000000e+00],
+ # [2.17284106e+03, 1.79985144e+03, 2.59600366e+03, 2.34515747e+03, 9.44890141e-01, 0.00000000e+00],
+ # [2.78233301e+03, 1.75100500e+03, 2.99900000e+03, 2.26862329e+03, 9.10233915e-01, 0.00000000e+00],
+ # [0.00000000e+00, 1.92825171e+03, 5.37962524e+02, 3.36087646e+03, 8.53242218e-01, 0.00000000e+00],
+ # [2.80115698e+03, 3.22995215e+03, 2.99900000e+03, 3.76810620e+03, 3.35420161e-01, 0.00000000e+00],
+ # [6.21354027e+01, 1.80441516e+03, 3.51005554e+02, 2.08294287e+03, 3.16491544e-01, 0.00000000e+00]]
+
+ z_t = []
+ liste_x = []
+ liste_y = []
+ nb_particle = 100
+ pos = [(2.5*rd.random(), 1.6*rd.random(), 2*3.14*rd.random()) for i in range(nb_particle)]
+ #pos = [(1.5, 1.180, 3.14/3) for i in range(nb_particle)]
+
+ for i in detection:
+ if i[4] >= seuil_cone:
+ x,y = boite2coord(i[0],i[1],i[2],i[3])
+ liste_x.append(x*2/3)
+ liste_y.append(y*2/3)
+
+ for i in range(len(liste_x)):
+ z_t.append((liste_x[i], liste_y[i]))
+
+
+ # x = np.linspace(0,2.5,100)
+ # y = np.linspace(0,1.6,100)
+ # X, Y = np.meshgrid(x,y)
+ # Z = np.zeros((100,100))
+ # for i in range(100):
+ # for j in range(100):
+ # Z[i,j] = sensor_update(z_t, (X[i,j],Y[i,j], 3.14/3))
+
+ # fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
+ # surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
+ # linewidth=0, antialiased=False)
+
+ plt.ion()
+ fig = plt.figure()
+ ax = fig.add_subplot(111)
+ exterieur = ax.plot(coord_x_ext, coord_y_ext,'+')
+ interieur = ax.plot(coord_x_int, coord_y_int,'+')
+
+
+ pos_x = [elt[0] for elt in pos]
+ pos_y = [elt[1] for elt in pos]
+ line1, = ax.plot(pos_x, pos_y, '.')
+ line2, = ax.plot(0,0,'o')
+ line3, = ax.plot(0,0,'o')
+
+ for i in range(100):
+
+
+ pos, W = particle_filter(pos, (0,0,1), z_t)
+ #W = [0.01 for i in range(100)]
+
+ pos_x = [0.0 for i in range(nb_particle)]
+ pos_y = [0.0 for i in range(nb_particle)]
+ pos_moy_x, pos_moy_y, pos_moy_theta = 0,0,0
+ cone_x, cone_y = [], []
+
+ for i in range(nb_particle):
+ pos_x[i] = pos[i][0]
+ pos_y[i] = pos[i][1]
+ pos_moy_x += W[i]*pos[i][0]
+ pos_moy_y += W[i]*pos[i][1]
+ pos_moy_theta += W[i]*pos[i][2]
+
+ for i in range(len(liste_x)):
+ x,y = rotation((liste_x[i] ,liste_y[i]), (0,0), pos_moy_theta)
+ cone_x.append(x+pos_moy_x)
+ cone_y.append(y+pos_moy_y)
+
+ line1.set_xdata(pos_x)
+ line1.set_ydata(pos_y)
+ line2.set_xdata(pos_moy_x)
+ line2.set_ydata(pos_moy_y)
+ line3.set_xdata(cone_x)
+ line3.set_ydata(cone_y)
+
+ fig.canvas.draw()
+
+ plt.pause(0.1)
'''
if __name__ == "__main__":
# pos = [(1.314, 1.162, 3.14/3.6) for i in range(10)]
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/__pycache__/MCL.cpython-38.pyc b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/__pycache__/MCL.cpython-38.pyc
index 3e9abd002e9cc0c5fc737a5ac50d3617e1d791de..143a98a285fc8e618c677c725b1ffde81f4d5358 100644
Binary files a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/__pycache__/MCL.cpython-38.pyc and b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/__pycache__/MCL.cpython-38.pyc differ
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/calibration.py b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/calibration.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb816ef09810d906c95ea7628edc4b0e91ec79b6
--- /dev/null
+++ b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/calibration.py
@@ -0,0 +1,36 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Mar 6 08:43:27 2023
+
+@author: paull
+"""
+
+import os
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+import cv2
+import numpy as np
+import tensorflow as tf
+from yolov3.utils import detect_image, detect_realtime, detect_video, Load_Yolo_model, detect_video_realtime_mp
+from yolov3.configs import *
+
+image_path = "./Calibration_cam/" #".jpg"
+video_path = "./IMAGES/test.mp4"
+
+yolo = Load_Yolo_model()
+
+distances = [0.5, 1, 2]
+h_pixel = []
+F = 0
+h_cone = 0.27
+
+for dist in distances:
+ path = image_path + str(dist) + "m.jpg"
+
+ print(path)
+
+ _, boxes = detect_image(yolo, path, "./Calibration_cam/out.jpg", input_size=YOLO_INPUT_SIZE, show=False, CLASSES=TRAIN_CLASSES, rectangle_colors=(255,0,0))
+
+ h_pixel.append(abs(boxes[0][1] - boxes[0][3]))
+ F += abs(boxes[0][1] - boxes[0][3])*dist/h_cone
+
+print(F/len(distances))
\ No newline at end of file
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/detection_custom.py b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/detection_custom.py
index 85cb50e7f38a5f4520422f199e900e484fa09459..c74a967a33cfbf7bf761f0574870f2ed44ab2871 100644
--- a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/detection_custom.py
+++ b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/detection_custom.py
@@ -16,14 +16,14 @@ import tensorflow as tf
from yolov3.utils import detect_image, detect_realtime, detect_video, Load_Yolo_model, detect_video_realtime_mp
from yolov3.configs import *
-image_path = "./Calibration_cam/2m.jpg"
+image_path = "./Calibration_cam/0.5m.jpg"
video_path = "./IMAGES/test.mp4"
yolo = Load_Yolo_model()
-#_, boxes = detect_image(yolo, image_path, "./Calibration_cam/0.5_detect.jpg", input_size=YOLO_INPUT_SIZE, show=True, CLASSES=TRAIN_CLASSES, rectangle_colors=(255,0,0))
+_, boxes = detect_image(yolo, image_path, "./images test/test2_pred.jpg", input_size=YOLO_INPUT_SIZE, show=True, CLASSES=TRAIN_CLASSES, rectangle_colors=(255,0,0))
#detect_video(yolo, video_path, './IMAGES/detected.mp4', input_size=YOLO_INPUT_SIZE, show=False, CLASSES=TRAIN_CLASSES, rectangle_colors=(255,0,0))
-detect_realtime(yolo, '', input_size=YOLO_INPUT_SIZE, show=True, CLASSES=TRAIN_CLASSES, rectangle_colors=(255, 0, 0))
+#detect_realtime(yolo, '', input_size=YOLO_INPUT_SIZE, show=True, CLASSES=TRAIN_CLASSES, rectangle_colors=(255, 0, 0))
#detect_video_realtime_mp(video_path, "Output.mp4", input_size=YOLO_INPUT_SIZE, show=True, CLASSES=TRAIN_CLASSES, rectangle_colors=(255,0,0), realtime=False)
-print(boxes[0][3]-boxes[0][1])
\ No newline at end of file
+print(boxes)
\ No newline at end of file
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164314.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test.jpg
similarity index 100%
rename from PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164314.jpg
rename to PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test.jpg
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164310.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test2.jpg
similarity index 100%
rename from PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164310.jpg
rename to PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test2.jpg
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test2_pred.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test2_pred.jpg
new file mode 100644
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diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164321.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test3.jpg
similarity index 100%
rename from PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164321.jpg
rename to PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test3.jpg
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164327.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test4.jpg
similarity index 100%
rename from PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164327.jpg
rename to PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test4.jpg
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164332.jpg b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test5.jpg
similarity index 100%
rename from PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/IMG_20230228_164332.jpg
rename to PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/images test/test5.jpg
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/utils.cpython-38.pyc b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/utils.cpython-38.pyc
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