Common Pitfalls to Avoid in Object Detection Datasets - Object Detection Challenges & Solutions

Learn about the best practices in creating high-quality datasets for Object Detection. “Data is the new Oil” — Unrefined and unpolished data will only result in a “GIGO” (Garbage In, Garbage Out) system!

Many Deep Learning practitioners ignore the importance of data quality while building the model and keep iterating over model building instead of improving their data. Here we discuss ideas on how to analyze your dataset and common pitfalls while creating the dataset. We also talk about how checking your data gives you insights into the quality of your dataset as well as tips on how to improve the data and, eventually, the model performance.

We take an example of a freely available public dataset to discuss the various issues that you may encounter while solving an Object Detection problem.

⭐️ Time Stamps ⭐️
0:00-00:22: Motivation
00:22-1:15: The Dataset
1:15-3:03: Analyzing the Dataset
3:03-4:29: Tip: Visualize the Dataset
4:29-6:14: Understanding the classes
6:14-7:54: Pitfall: Oversampling frames from a video
7:54-11:36: Data Variance vs Data Size
11:36-11:57: Tip: Compare Training and Validation Set
11:57-14:35: Training Validation Overlap
14:35-16:01: Tip: Check Data Statistics
16:01-17:01: Pitfall: Class Imbalance
17:01-20:33: Visualize Data Annotations
20:33-21:34: Pitfall: Miscalssified or Incorrect Labels
21:34-27:03: Pitfall: Missing / Wrong Labels
27:03-29:22 : Pitfall: inconsistent labels
29:22-31:11 : Summary

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[vineetsharma]

Thanks Sir for this informative video. The content of this Video is pure gold.

I have been doing the Exploratory Data Analysis and Overlays for a while and many times people think it is a waste of time to go at such granular level to visually examine the data.

Now, I have your this video to prove my point.😊

Thanks Sir. 🙏

[cyberhard]

Great video! While the background music isn't loud, to my ears, it is a little intrusive and not needed.

[arjoai]

It was greatly helpful. Glad that you uploaded it!

[afjamo]

I like this video! It answered a lot of questions I had as a beginner. Thank you so much!

One question. This video is mainly about bounding box annotation. What about with key-point annotation? I am going to annotate mice in a cage, which means the objects are highly occluded. But I would like to use key-point annotation to detect their behaviour. What would be the best way to annotate to be consistent do you think?

[LearnOpenCV]

Time Stamps:
0:00-00:22: Motivation
00:22-1:15: The Dataset
1:15-3:03: Analyzing the Dataset
3:03-4:29: Tip: Visualize the Dataset
4:29-6:14: Understanding the classes
6:14-7:54: Pitfall: Oversampling frames from a video
7:54-11:36: Data Variance vs Data Size
11:36-11:57: Tip: Compare Training and Validation Set
11:57-14:35: Training Validation Overlap
14:35-16:01: Tip: Check Data Statistics
16:01-17:01: Pitfall: Class Imbalance
17:01-20:33: Visualize Data Annotations
20:33-21:34: Pitfall: Miscalssified or Incorrect Labels
21:34-27:03: Pitfall: Missing / Wrong Labels
27:03-29:22 : Pitfall: inconsistent labels
29:22:31:11 : Summary

[atmadeeparya]

Excellent video. I realized I made multiple mistakes during the first iteration of my training. I currently focusing on creating a better dataset which is more representative.

[masterkraft]

hi ! thank you for this video, it's great. What software do you use to label ? Thanks

[zy.r.]

Thank u for the video! How should be prepared dataset for long or short objects passing on conveyor belt?

[seanolivieri]

In medical images, I used augmentation. Do you think that augmentation pollutes sets? I used 3 augs per image + I had some frames from the same video so I am going to change that (plus those where augmented)

[iramarshad]

Hi Opencv, can you share the data stats code which is used in this example?

[QuarktaschemitSenf]

I have one very urgent question. Meanwhile i was successfull in running yolo on my local gpu and training on it. But all the tutorials just show how to create a custom dataset with 1 or 2 classes. How would i add my custom datatset to an already existing like the coco one? Can you help?

[FirstNameLastName-fveu]

COme on man!! we know this data can only make someone "Youtube DataScientist", you need to have minimum 20000-40000 Images per label to build the model with 70+ accuracy THAT YOU CAN SELL!!! This data is only to impress your gf :)

[LearnOpenCV]

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