How to train SSD MOBILENET DRAGON for Custom Object Detection for #jetson #nano

Train SSD MOBILENET

In this video, we will see how we can train SSD-MOBILENET model for your own custom object detection. For this video, we have used images for apples and banana and we have trained a model for this. Training has been performed on Ubuntu machine and then we have used #jetson #xavier to run that model.

Watch other custom training videos :

In this video, we will see how we can train SSD-MOBILENET model for your own custom object detection. For this video, we have used images for apples and banana and we have trained a model for this. Training has been performed on Ubuntu machine and then we have used #jetson #xavier to run that model.

If you want to train your own model, follow the steps mentioned in the repository and you will be able to train your model very easily.

Introduction : (0:00)
Understanding training project: (0:36)
Prepare dataset: (3:14)
Annotation : (5:58)
Create labels file : (9:51)
Training your dragon : (10:27)
Training graph : (13:30)
Using the best dragon : (14:50)
Extracting ONNX file on Jetson : (15:55)
Extracting engine file on Jetson : (17:35)
Inferencing : (19:03)

[juancarlosruedaquezada]

Thanks you so much. I was looking for this a lot of time.

[fawwazyo]

Is it okay if we train the same data but Separately becauss not enough space on ubuntu laptop, and then the the result will be used as well for the same detection?

[mendoncapedro]

Thank you for the tutorial. How can i extract the mAP0.5 and training loss together?

[rajmeetsingh]

thanks for sharing. Is there any pre installation required for some libraries. There were lots of input error during training script.

[Deepsim]

Great tutorial, thanks. But how can we print the coordinates (x, y and the centre point) of each object.

[Unfreeze]

I'm getting an error of no module named torch.fx
whereas it is installed.

also how to train using GPU instead of CPU which is happening by default.

[HimanshuKumar-crmw]

hi i just wanted to ask are we using ssd mobile net v2 or just ssd mobilenet
Thankyou

[boru]

Thanks for the video. I have a couple of questions you have set the epochs=500 at 12:00 but you get the best checkpoint at 963. epoch at 15:33. How does that happen? You trained more after 500. epoch if so which command you have used? Could you please help me?

[jeevanjayakumar]

I got my less loss model, i just need to check with other input image for checking the model using in colab. i got confussed from .pth file onwards. i didn't install/ download jeton files

[sylvesterthethird]

Hello after training my custom datasheet and exporting it to onnx it give me an error ssting OSERROR: couldnt fund valid .pth checkpoint under 'models/TuodMango'

[kmlsensors-cp]

hi i m getting error when i m doing my image training using my pc which has a gpu and the error is "Traceback (most recent call last):
File "train_ssd.py", line 13, in <module>
from torch.utils.tensorboard import SummaryWriter
File "/home/kml/rohin/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py", line 1, in <module>
import tensorboard
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/__init__.py", line 4, in <module>
from .writer import FileWriter, SummaryWriter
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/writer.py", line 28, in <module>
from .summary import scalar, histogram, image, audio, text
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/summary/__init__.py", line 22, in <module>
from tensorboard.summary import v1 # noqa: F401
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/summary/v1.py", line 21, in <module>
from tensorboard.plugins.audio import summary as _audio_summary
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/plugins/audio/summary.py", line 34, in <module>
from tensorboard.plugins.audio import metadata
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/plugins/audio/metadata.py", line 18, in <module>
from tensorboard.compat.proto import summary_pb2
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/compat/proto/summary_pb2.py", line 17, in <module>
from tensorboard.compat.proto import histogram_pb2 as
File "/home/kml/rohin/lib/python3.8/site-packages/tensorboard/compat/proto/histogram_pb2.py", line 18, in <module>
DESCRIPTOR = _descriptor.FileDescriptor(
File "/home/kml/rohin/lib/python3.8/site-packages/google/protobuf/descriptor.py", line 1024, in __new__
return
TypeError: Couldn't build proto file into descriptor pool!
Invalid proto descriptor for file
is already defined in file
is already defined in file
is already defined in file
is already defined in file
is already defined in file
is already defined in file
is already defined in file
tensorboard.HistogramProto: "tensorboard.HistogramProto" is already defined in file

[quocduytran]

i have a question. How to fix to choose the model"mb2-ssd-lite"? and Can you give me the "mb2-ssd-lite-mp-0_686.pth"? I have a bug tu train. Please!!

[shalawmshir]

can convert the trained model to frozen_inference_graph.pb?

[yeppeun]

hi what if you already have jpeg files and dont need to extract from a video? I want to create those directories but i dont know the script.

[slashplusdash]

do I need to use ubuntu OS for this or is Windows OS okay?

[mohammedazzan]

hello can you please provide me a link for pre trained data sets?

[AICSAnushaBhat]

Hye
I need to make mobile application for food nutrition detection using ai for diabetic patients .. Can you help me to achieve this!?

[tilmahutli]

I have this error, you can helpme, please?

2023-06-28 14:00:55 - Epoch: 0, Step: 10/60, Avg Loss: 77.0541, Avg Regression Loss 66.9335, Avg Classification Loss: 10.1206
2023-06-28 14:01:00 - Epoch: 0, Step: 20/60, Avg Loss: 72.4313, Avg Regression Loss 64.5434, Avg Classification Loss: 7.8879
2023-06-28 14:01:07 - Epoch: 0, Step: 30/60, Avg Loss: 74.7886, Avg Regression Loss 67.5160, Avg Classification Loss: 7.2726
2023-06-28 14:01:12 - Epoch: 0, Step: 40/60, Avg Loss: 65.2462, Avg Regression Loss 60.2236, Avg Classification Loss: 5.0226
2023-06-28 14:01:18 - Epoch: 0, Step: 50/60, Avg Loss: 80.1739, Avg Regression Loss 75.2484, Avg Classification Loss: 4.9255
2023-06-28 14:01:23 - Epoch: 0, Training Loss: 78.1188, Training Regression Loss 71.2975, Training Classification Loss: 6.8214
Traceback (most recent call last):
File "/content/jetson-train-main/train_ssd.py", line 400, in <module>
val_loss, val_regression_loss, val_classification_loss = test(val_loader, net, criterion, DEVICE)
File "/content/jetson-train-main/train_ssd.py", line 200, in test
regression_loss, classification_loss = criterion(confidence, locations, labels, boxes)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/content/jetson-train-main/vision/nn/multibox_loss.py", line 41, in forward
classification_loss = F.cross_entropy(confidence.reshape(-1, num_classes), labels[mask], size_average=False)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/functional.py", line 3029, in cross_entropy
return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index, label_smoothing)
IndexError: Target 4 is out of bounds.

[atikayunisaanadia]

[cuda] cudaEventElapsedTime(&cuda_time, mEventsGPU[evt], mEventsGPU[evt+1])
[cuda] device not ready (error 600) (hex 0x258)
[cuda]