casafurix / yolo-distance-estimation

Distance estimation using YOLO.

TO DO

• Finding distance of mutiple object at same time.

Installation you need opencv-contrib-python

opencv contrib

windows

pip install opencv-contrib-python==4.5.3.56

Linux or Mac

pip3 install opencv-contrib-python==4.5.3.56

then just clone this repository and you are good to go.

I have use tiny weights, check out more on darknet github for more

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Add more Classes(Objects) for Distance Estimation

You will make changes on these particular lines DistanceEstimation.py

if classid ==0: # person class id
    data_list.append([class_names[classid[0]], box[2], (box[0], box[1]-2)])
elif classid ==67: # cell phone
    data_list.append([class_names[classid[0]], box[2], (box[0], box[1]-2)])

# adding more classes for distnaces estimation

elif classid ==2: # car
    data_list.append([class_names[classid[0]], box[2], (box[0], box[1]-2)])

elif classid ==15: # cat
    data_list.append([class_names[classid[0]], box[2], (box[0], box[1]-2)])
# in that way you can include as many classes you want

    # returning list containing the object data.
return data_list

Reading images and getting focal length

You have to make changes on these lines 📝 DistanceEstimation.py there two situations, if the object(classes) in single image then, here you can see the my reference image <img src='ReferenceImages/image4.png' width=200> it has to two object, person and cell phone

# reading refrence images
ref_person = cv.imread('ReferenceImages/image14.png')
ref_mobile = cv.imread('ReferenceImages/image4.png')
# calling the object detector function to get the width or height of object
# getting pixel width for person
person_data = object_detector(ref_person)
person_width_in_rf = person_data[0][1]

# getting pixel width for cell phone
mobile_data = object_detector(ref_mobile)
mobile_width_in_rf = mobile_data[1][1]

# getting pixel width for cat
cat_data = object_detector(ref_person)
cat_width_in_rf = person_data[2][1]

# getting pixel width for car
car_data = object_detector(ref_person)
car_width_in_rf = person_data[3][1]

if there is single class(object) in reference image then you approach it that way 👍

# reading the reference image from dir
ref_person = cv.imread('ReferenceImages/person_ref_img.png')
ref_car = cv.imread('ReferenceImages/car_ref_img.png.png')
ref_cat = cv.imread('ReferenceImages/cat_ref_img.png')
ref_mobile = cv.imread('ReferenceImages/ref_cell_phone.png')

# checking object detection on reference image
# getting pixel width for person
person_data = object_detector(ref_person)
person_width_in_rf = person_data[0][1]

# getting pixel width for cell phone
mobile_data = object_detector(ref_mobile)
mobile_width_in_rf = mobile_data[0][1]

# getting pixel width for cat
cat_data = object_detector(ref_cat)
cat_width_in_rf = person_data[0][1]

# getting pixel width for car
car_data = object_detector(ref_car)
car_width_in_rf = person_data[0][1]
# then you find Focal length for each