Custom Object Detection Using YOLOv7 & Python 💯 | Coding Tutorial

Object detection has been studied for a long time with increasingly better prediction results. Usually, large datasets are required to get good results. In this video, we will use the pre-trained YOLOv7 model and fine-tune it on our custom dataset to recognize our custom object. As I will show in the video, really good results can be achieved with as few as 16 training images.

00:00:00 Intro
00:00:21 Getting Started
00:01:23 Data Collection
00:03:28 Labelling
00:07:37 Dataset Formatting
00:12:09 Training YOLOv7 Model
00:17:40 Detecting Your Own Class
00:23:05 Outro

Links Used in This Video

Colab Notebook:

Pixabay:

Label Studio:

YOLOv7 Repository:

YOLOv7 Open Issue:

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I hope this video helped you to achieve awesome object detection results :) If so, feel free to share your success story in the comment section, but also if you have questions or ideas. Any like or subscription is very much appreciated 🙏🏻

[WorldEnder]

can this detect in real time from a webcam video feed? could be used as a sorter for some kind of machinery to select ripe fruits or smth

[khenpahilanga]

Hello sir, do u think this technique is enough to identify different leaf plant diseases? I wanna create a system that could identify the different diseases realtime, do u think u could give me advice, im kinda not good at programming? Thanks for your video

[alexanderbolton]

Thanks for this video. Do you know a way of detecting objects in a 3D scene rather than a 2D picture? For example, finding standard equipment in a 3D scan of a factory?

[jzpwxii]

hlo sir i have one doubt how can i change the epoch size because 300 is big for me

[johanneskoppe]

Awesome. Can u do a video about darts detection too?

[walidflux]

thanks for the video but what is the point of detcting exactly? it is worthless if there is no data with it

[johanletter]

I have nothing to do with all these coding and AI things. But I watch every single video in your channel because you're so handsome and cute :))) You're exactly my type. Sorry because I can't understand your shared knowledge, but I will keep watching your videos. Hope I can get your Instagram or any other social medias, just to follow as a fan 🥺

[janviaggarwal]

hey thanks for the video. I tried it but i. am getting this error.Can you please help me



Traceback (most recent call last):
File "/content/yolov7/train.py", line 616, in <module>
train(hyp, opt, device, tb_writer)
File "/content/yolov7/train.py", line 64, in train
data_dict = yaml.load(f, Loader=yaml.SafeLoader) # data dict
File "/usr/local/lib/python3.8/dist-packages/yaml/__init__.py", line 81, in load
return loader.get_single_data()
File "/usr/local/lib/python3.8/dist-packages/yaml/constructor.py", line 49, in get_single_data
node = self.get_single_node()
File "/usr/local/lib/python3.8/dist-packages/yaml/composer.py", line 36, in get_single_node
document = self.compose_document()
File "/usr/local/lib/python3.8/dist-packages/yaml/composer.py", line 55, in compose_document
node = self.compose_node(None, None)
File "/usr/local/lib/python3.8/dist-packages/yaml/composer.py", line 84, in compose_node
node =
File "/usr/local/lib/python3.8/dist-packages/yaml/composer.py", line 127, in compose_mapping_node
while not
File "/usr/local/lib/python3.8/dist-packages/yaml/parser.py", line 98, in check_event
self.current_event = self.state()
File "/usr/local/lib/python3.8/dist-packages/yaml/parser.py", line 428, in parse_block_mapping_key
if self.check_token(KeyToken):
File "/usr/local/lib/python3.8/dist-packages/yaml/scanner.py", line 115, in check_token
while self.need_more_tokens():
File "/usr/local/lib/python3.8/dist-packages/yaml/scanner.py", line 152, in need_more_tokens

File "/usr/local/lib/python3.8/dist-packages/yaml/scanner.py", line 291, in stale_possible_simple_keys
raise ScannerError("while scanning a simple key", key.mark,
yaml.scanner.ScannerError: while scanning a simple key
in "/content/dataset/coco.yaml", line 7, column 1
could not find expected ':'
in "/content/dataset/coco.yaml", line 8, column 1