YOLO Object Detection Using OpenCV And Python || Python Project

YOLO Object Detection Using OpenCV And Python Complete Project || YOLO Object Detection from Scratch || Computer Vision Projects.
🔥 For Project resources, Click The Link below :
bit.ly/3GLJkYs
In this lesson we will learn YOLO Object Detection Using OpenCV And Python Complete Project.
Real - Time Object Detection
In this project we are building real time object detection where we will detect the object in real time. In this course course we trained 20 different object those are 'person', 'car', 'chair', 'bottle', 'pottedplant', 'bird', 'dog', 'sofa', 'bicycle', 'horse', 'boat', 'motorbike', 'cat', 'tvmonitor', 'cow', 'sheep', 'aeroplane', 'train', 'diningtable' and 'bus'.
In order to achieve this we will follow the Data Science SDLC (Software Development Life Cycle). First we will start by gathering the data and requirements. After that based on the requirements we will create the pipeline to prepare the data.
Once our data is ready then we will train our YOLOv5 model in Google Collab GPU environment. Finally we will extract the detection from the model.
Welcome to this comprehensive tutorial on YOLO (You Only Look Once) Object Detection using OpenCV and Python. In this video, you will learn how to implement the state-of-the-art deep learning model YOLO to detect objects in images and videos.
Here's what you will learn in this tutorial:
Introduction to YOLO object detection
Installing OpenCV and other required libraries
Preparing the dataset and annotations for training
Training the YOLO model using Darknet
Fine-tuning the pre-trained YOLO model for better accuracy
Testing the trained model on images and videos
Visualizing the results and tuning the parameters for better performance
Whether you're a beginner or an advanced user, this tutorial will guide you through every step of the process, from setting up the environment to training the model and testing it on real-world data.
At the end of this video, you will have a deep understanding of how YOLO works and how you can apply it to solve real-world problems. So, if you're ready to take your computer vision skills to the next level, hit the play button and let's get started!
Don't forget to like, share, and subscribe to our channel for more tutorials on computer vision, machine learning, and deep learning.
Thank you for watching!

[@user-hu9qt9rm6l]

Thank you Sir for this project Great Explanation

[@AmanShah-qt9zz]

Thank you sir for this project

[@onlinestore911]

great work 👍

[@nabinshrestha2095]

Great❤❤❤ learning . Its super helpful

[@SKNLOGISTICS]

Great Work

[@emailnizmai-cu3kw]

Great course❤

[@AliyaMaqsood-pg2wl]

Great course 👍

[@kelixoderamirez]

permission to learn sir. thank you

[@brentcos9370]

You mentioned that the images are available in the "resources". Where is that? I'd like to download all of them so I can follow along with your tutorial.

[@geoscieducation8001]

Amazing Video, Thank you for sharing this video.

[@dasa9639]

laura

[@shwetabhat9981]

Amazing resource 👍 Thank you for this !! Looking forward to many more 🙂

[@gyaneshwar7647]

can you share the resources with me? i can't images..please help me

[@anjali7159]

That's an amazing video sir...can we do the same in other IDEs like Vs code so that I can create user interface for the same model.

[@urakondasaikumar1002]

Thank you sir! your explanation is simply amazing.....

[@dasa9639]

laura

[@PushkarPatel-404]

Absolutely loved the video. I just had one question, how do i export this project and run it locally ?

[@OpenSourceDesign]

This is great, can you share the project/github?

[@user-wj8hx2mz4y]

Thank you so much. Your video is great for beginers like me

[@dasa9639]

laura

[@ahmadshabaz2724]

Great tutorial thanks a lots. Much respect you sir.

[@dasa9639]

laura

[@thekidwithadream]

The google drive link is not working kindly look into it as I am not able to see the images you used

[@ikbajpai8054]

same here

[@leonidas1983]

Excellent work! Congrats

[@dasa9639]

laura

[@monstergamerz2343]

your video is very nice it is showing not responding on running cv2.imshow('yolo_prediction,image) what to do please help

[@berozzzgaarengineer]

i got error when img_pred = yolo.prediction(img ) unsupport operand type(s) for :-

[@abdulrasheedabdulmajeed5997]

Can't find the image file the google drive link is not working

[@SuryaM-uj2gs]

thanks for helping .. but resources is not opening in google drive .. data images .please can you share that

[@uttarakhandpcsbaba2608]

Please make a video on yolov8

[@alesyamoroz3357]

Great!!! Thank you so much!!!

[@yafisraza1210]

Hi can u help me in this project...

[@yafisraza1210]

U have complete this project...

[@monstergamerz2343]

it is showing not responding on running cv2.imshow('yolo_prediction,image) what to do

[@muhammadsabrimas2016]

how to printed total object count and fps on the image/video?

[@nasrathrihana1608]

Can you please tell me how to use this model for real time detection using webcam

[@raghavuppal2512]

how can i integrate this code with a python program that shows traffic light system in which it turn the light to green once it detects the ambulance on the junction

[@MuhammadAdnan-tq3fx]

this GPU facilities only for one time ???

[@paulpolizzi3421]

can this be used in a soccer game for stats?

[@nasrathrihana1608]

I'm getting error while loading yolo model in onnx format in yolo_predictions.ipynb

[@deeranify]

Can u do a video about detectron2

[@RahulSahu-hp1kz]

What changes i have to make in order to make it a real time object detector?????

[@samarasinghesupunc]

can we use the web cam also?

[@ahmedsaliem7041]

If I had label = V457P08219 for a dataset of images, how to encode this label ???? Please, I need an answer. Thanks.

[@asadullahyousaf1638]

can you please share the image data drive link, the given is not working

[@faroozrimaaz7092]

Can you please provide the data images folder properly..in resources you have given it shows the page is not found

[@jainchaitanya1511]

did u find the data images folder?

[@ahmedsaliem7041]

what's error in this when run the final part of video this error pop up= AttributeError: 'tuple' object has no attribute 'flatten' in line 80 pf python file ????

[@user-fy4gs3ee3h]

Hey, Can you please provide the link to data-images. The one which you provided in the resources is not working. please, please... it will help a lot. Thank you so much

[@gyaneshwar7647]

did you get the data images? please help me too

[@alhashedi543]

thank you for your great effort. but unfortunately the data images URL you provide does not exist. please re sent the correct URL

[@thekidwithadream]

True, so are you waiting for data folder or you just created your own?

[@alhashedi543]

@@thekidwithadream waiting for data folder

[@user-fy4gs3ee3h]

Hey did, you made your own ? Could you please share me.. Thank you in advance

[@GauravSingh-zt4us]

hello sir images folder doesnt exist message pop up please update the latest images folder

[@ganeshprasadgs5456]

Sir image resources link is not working

[@sreebalaji362]

How to check the accuracy of the model pls tell me sir

[@asosalih257]

there is no image resources, please give us its link

[@schre6171]

i cant find the data images can you please give the links thanks you very much

[@ngsteachingonline1181]

Google drive folder image page not found

[@rahulsingha1542]

i am getting error in real time object detection saying attributte error saying 'tuple' object has no attribute 'flatten' can someone help

[@Cronus67]

Did you solve that i am also getting the same error

[@ankushkumar-rk8hs]

from where we can get the code for this

[@donjoseph5980]

where to find the resources

[@imtiazahmad4456]

where is image data?

[@user-bd2dr8fq6o]

can I get your dataset?

[@ikbajpai8054]

I am not able to download images

[@RahulSahu-hp1kz]

How i make real time object detector by webcam

[@gyaneshwar7647]

I am unable to get data images, can anyone please help me?

[@gunturugopikrishna1824]

Hi can you pls send me labeled images

[@yashkinha7386]

Image_data is not avallable

[@bennishben950]

while doing label encoading # label encoding def label_encoding(x): labels = {'person':0, 'car':1, 'chair':2, 'bottle':3, 'pottedplant':4, 'bird':5, 'dog':6, 'sofa':7, 'bicycle':8, 'horse':9, 'boat':10, 'motorbike':11, 'cat':12, 'tvmonitor':13, 'cow':14, 'sheep':15, 'aeroplane':16, 'train':17, 'diningtable':18, 'bus':19} return labels[x] train_df['id'] = train_df['name'].apply(label_encoding) test_df['id'] = test_df['name'].apply(label_encoding) this error occurs --------------------------------------------------------------------------- KeyError Traceback (most recent call last) Cell In[30], line 1 ----> 1 train_df['id'] = train_df['name'].apply(label_encoding) 2 test_df['id'] = test_df['name'].apply(label_encoding) File E:\YoloV8\yolo_object_detection\Notes\yolo_venv\Lib\site-packages\pandas\core\series.py:4630, in Series.apply(self, func, convert_dtype, args, **kwargs) 4520 def apply( 4521 self, 4522 func: AggFuncType, (...) 4525 **kwargs, 4526 ) -> DataFrame | Series: 4527 """ 4528 Invoke function on values of Series. 4529 (...) 4628 dtype: float64 4629 """ -> 4630 return SeriesApply(self, func, convert_dtype, args, kwargs).apply() File E:\YoloV8\yolo_object_detection\Notes\yolo_venv\Lib\site-packages\pandas\core\apply.py:1025, in SeriesApply.apply(self) 1022 return self.apply_str() 1024 # self.f is Callable -> 1025 return self.apply_standard() File E:\YoloV8\yolo_object_detection\Notes\yolo_venv\Lib\site-packages\pandas\core\apply.py:1076, in SeriesApply.apply_standard(self) 1074 else: 1075 values = obj.astype(object)._values -> 1076 mapped = lib.map_infer( 1077 values, 1078 f, 1079 convert=self.convert_dtype, 1080 ) 1082 if len(mapped) and isinstance(mapped[0], ABCSeries): 1083 # GH#43986 Need to do list(mapped) in order to get treated as nested 1084 # See also GH#25959 regarding EA support 1085 return obj._constructor_expanddim(list(mapped), index=obj.index) File E:\YoloV8\yolo_object_detection\Notes\yolo_venv\Lib\site-packages\pandas\_libs\lib.pyx:2834, in pandas._libs.lib.map_infer() Cell In[26], line 6, in label_encoding(x) 2 def label_encoding(x): 3 labels = {'person':0, 'car':1, 'chair':2, 'bottle':3, 'pottedplant':4, 'bird':5, 'dog':6, 4 'sofa':7, 'bicycle':8, 'horse':9, 'boat':10, 'motorbike':11, 'cat':12, 'tvmonitor':13, 5 'cow':14, 'sheep':15, 'aeroplane':16, 'train':17, 'diningtable':18, 'bus':19} ----> 6 return labels[x] KeyError: 'Person' how to resolve this

[@darthyrabecka1472]

D:\UDEMY\TRAIN YOLO FOR OBJECT DETECTION\yolo_venv>Scripts\activate (yolo_venv) D:\UDEMY\TRAIN YOLO FOR OBJECT DETECTION\yolo_venv>pip install -r requirements.txt ERROR: Could not open requirements file: [Errno 2] No such file or directory: 'requirements.txt'

[@WolfofScience]

requirements.txt is your file's name. you need to use it requirements.txt.txt or just erase the ".txt" part from file name

[@ben10_prvn]

This is the error getting. can you plz help me out error Traceback (most recent call last) in 1 # load YOLO model 2 ----> 3 yolo = cv2.dnn.readNetFromONNX("./Model/weights/best.onnx") 4 yolo.setPreferableBackend(cv2.dnn.DNN_BACKEND_OPENCV) 5 yolo.setPreferableBackend(cv2.dnn.DNN_TARGET_CPU) error: OpenCV(4.5.3) D:\bld\libopencv_1632857399304\work\modules\dnn\src\onnx\onnx_importer.cpp:2146: error: (-2:Unspecified error) in function 'cv::dnn::dnn4_v20210608::ONNXImporter::handleNode' > Node [Split]:(/model.24/Split_output_0) parse error: OpenCV(4.5.3) D:\bld\libopencv_1632857399304\work\modules\dnn\src\layers\slice_layer.cpp:187: error: (-215:Assertion failed) splits > 0 && inpShape[axis] % splits == 0 in function 'cv::dnn::SliceLayerImpl::getMemoryShapes' >

[@mdarafatrahmankhan8602]

This occurs when you are exporting the model in best.onnx format. Try using export your model by setting opset and image length and width and hope your problem will be solved.

[@user-gr3vk5bt3w]

great work 👍

[@ihebakermi943]

where is image data?