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
new file mode 100644
index 0000000000000000000000000000000000000000..3b2f09ab135d9b1029dc1fb1a6fdbe3e40c5a5f9
Binary files /dev/null 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/MCL.py b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/MCL.py
index 4cd5bdff5968efbe0278dc948566f51359df8384..ee5961f9bd32efd43fdd74c993594a22eef03cbb 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
@@ -35,9 +35,9 @@ 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 = 3423 #Focale camera
-h_reel = 0.234 #Hauteur d'un plot
-y_0 = 1500 #Milieu de l'image
+F = 3951 #Focale camera
+h_reel = 0.24 #Hauteur d'un plot
+y_0 = 2000 #Milieu de l'image
dist_roue = 0.25 #Distance entre les roues avant et les roues arrieres
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 6d426f2f120b2cedea24a7901344d108cb3b8225..3e9abd002e9cc0c5fc737a5ac50d3617e1d791de 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/detection_custom.py b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/detection_custom.py
index 1339cdf2c1f3b899fc910d2cbd5f177fc1b0cf13..d0b0931b7d092797e28ae5094e21e1e2c3eba1a5 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
@@ -16,12 +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 = "./IMAGES/cone.jpg"
+image_path = "./Calibration_cam/2m.jpg"
video_path = "./IMAGES/test.mp4"
yolo = Load_Yolo_model()
-#detect_image(yolo, image_path, "./IMAGES/cone_detect.jpg", input_size=YOLO_INPUT_SIZE, show=True, CLASSES=TRAIN_CLASSES, rectangle_colors=(255,0,0))
+_, 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))
#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
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/car_interface.cpython-38.pyc b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/car_interface.cpython-38.pyc
index 42a176b8d8bb0c9261b4e02d27862a2afb159d44..96da68506c9441435bb10e90ecfbd9c1c4333b54 100644
Binary files a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/car_interface.cpython-38.pyc and b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/car_interface.cpython-38.pyc differ
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/pilote.cpython-38.pyc b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/pilote.cpython-38.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..74cbae8c165706725bb686715d223136ba6ee5f7
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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
index 0275e8b4bf7d538834dfabcacacade777e7185ea..24998a2546bac92ce81cd7aab30ab4b1fb254fc3 100644
Binary files a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/utils.cpython-38.pyc and b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/__pycache__/utils.cpython-38.pyc differ
diff --git a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/utils.py b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/utils.py
index 22ca2bd41515cbfff1e5306bbf5aa84a8a248102..afdd82e4044601404d014daddd222e8023be8109 100644
--- a/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/utils.py
+++ b/PAR 152/Yolo V3/TensorFlow-2.x-YOLOv3-master/yolov3/utils.py
@@ -146,7 +146,7 @@ def image_preprocess(image, target_size, gt_boxes=None):
return image_paded, gt_boxes
-def draw_bbox(image, bboxes,liste_pos_car, CLASSES=YOLO_COCO_CLASSES, show_label=True, show_confidence = True, Text_colors=(255,255,0), rectangle_colors='', tracking=False, ser=None, previous_command=(0,0)):
+def draw_bbox(image, bboxes,liste_pos_car=liste_pos((0,0,0),1), CLASSES=YOLO_COCO_CLASSES, show_label=True, show_confidence = True, Text_colors=(255,255,0), rectangle_colors='', tracking=False, ser=None, previous_command=(0,0,1)):
NUM_CLASS = read_class_names(CLASSES)
num_classes = len(NUM_CLASS)
image_h, image_w, _ = image.shape
@@ -370,7 +370,7 @@ def detect_image(Yolo, image_path, output_path, input_size=416, show=False, CLAS
bboxes = postprocess_boxes(pred_bbox, original_image, input_size, score_threshold)
bboxes = nms(bboxes, iou_threshold, method='nms')
- image = draw_bbox(original_image, bboxes, CLASSES=CLASSES, rectangle_colors=rectangle_colors)
+ image,_,_,_ = draw_bbox(original_image, bboxes, CLASSES=CLASSES, rectangle_colors=rectangle_colors)
# CreateXMLfile("XML_Detections", str(int(time.time())), original_image, bboxes, read_class_names(CLASSES))
if output_path != '': cv2.imwrite(output_path, image)
@@ -382,7 +382,7 @@ def detect_image(Yolo, image_path, output_path, input_size=416, show=False, CLAS
# To close the window after the required kill value was provided
cv2.destroyAllWindows()
- return image
+ return image, bboxes
def Predict_bbox_mp(Frames_data, Predicted_data, Processing_times):
gpus = tf.config.experimental.list_physical_devices('GPU')