Train YOLOv7 On Custom Dataset | Object Detection |

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Video demonstrates the implementation of the YOLOv7 object detection algorithm on your custom dataset from scratch.

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Thanks for the detailed video. Really very helpful

manusid
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Deserves more like & share, next video could be on how to contenarize & deploy as app !

SP-dbsh
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hi, you made a wonderful video really it is amazing i thankful to you
after training when i try to detect the object it doesn't show any bounding boxes ...
could you plz tell me what is the problem

himanthrayagada
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Thanks for the amazing tutorial. Can you make a video on how to load a model or how to use it on real time using our webcam?

abdelhamidazanzal
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hello, how do i perform transfer learning, this is the term for adding more training to my pre-trained custom dataset right?

zombiefreak
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Sir jb hum testing krte hai to bounding boxes nhi aa rhe hai, how can we solve this problem? 😔

MangeshKhode-hn
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Hi, Tha, k you, is there any way to use .pt file with Opencv

mangaenfrancais
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Sir, can you please tell me how to calculate the overall accuracy of the particular trained yolov7 model after testing an image in Google colab.

akshayakki
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why test.py testing the validation images? why not test images instead?

mhmahfuz
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hi guys how can i find pretrained weigths set like a hardhalmet pretrained set

RayLightsSensor
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Hi!

I have a dataset including images with different sizes and their annotations are created based on these sizes (bounding boxes, for example), can I use Yolov7 to train this dataset?

I also see that your label file contains (class x y z o), could you please tell which one is x_min, x_max, y_min and y_max among those x, y, z, o?

Thanks.

yamei
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Great tutorial, can you also tell what should i do to resolve error like "AssertionError: train: No labels in created custom dataset on dogs and cats classification with labelimg @karndeep Singh

pranavchakne
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I have an error while trying to import dataset from my drive




MessageError Traceback (most recent call last)
in <module>
1 from google.colab import drive
----> 2

3 frames
in read_reply_from_input(message_id, timeout_sec)
100 reply.get('colab_msg_id') == message_id):
101 if 'error' in reply:
--> 102 raise MessageError(reply['error'])
103 return reply.get('data', None)
104

MessageError: Error: credential propagation was unsuccessful

mbahabilen