Android app crashes

[parmarth-1208]

When we run android app using float32 tflite model which we trained on image size 640 and yolov8m the app crashes so is it because of the size and yolov8m or what can be the problem im already trying to re-train my model on yolov8n and size 265 so will this solve my issue?

[surendramaran]

I understand, just use a resolution which is divisible by 32.

Try to train in that way.

Share with me your model's input and output shapes, In case you don't know then Go to https://netron.app And upload your model, then click on the properties and share the input and output shape .

On Fri, 15 Mar, 2024, 2:38 PM parmarth-1208, @.***> wrote:

When we run android app using float32 tflite model which we trained on image size 640 and yolov8m the app crashes so is it because of the size and yolov8m or what can be the problem im already trying to re-train my model on yolov8n and size 265 so will this solve my issue?

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[parmarth-1208]

tensor: float32[1,640,640,3] input shape tensor: float32[1,14,8400] output shape

[surendramaran]

Any update on the new model? or share crash logs. The input and output shapes looks fine.

[parmarth-1208]

tensor: float32[1,256,256,3] input shape tensor: float32[1,40,1344] output shape The Android crashes within few seconds without detection what can be the issue images resolution is also 256 and yolov8n model.

[surendramaran]

Can you check your lebal.txt file is it in the same format as it is in this repository, if this is fine then please share with me your model and the lebal.txt file to my email surendramaran8@gmail.com

[parmarth-1208]

Hey done with the Android, thankyou for your help. Actually I'm developing a anpr system and in order to maintain a datasheet of detected number plates I'm coding the detection and storage process. For that I want path of "yolov8.weights" and "yolov8.cfg" I'm not getting what path should I replace this with if possible please help

[surendramaran]

Unfortunately I have not heard of these terms. If you can refrence any documentation regarding this, maybe I will understand.

[HimangsKalita]

Can you check your lebal.txt file is it in the same format as it is in this repository, if this is fine then please share with me your model and the lebal.txt file to my email surendramaran8@gmail.com

I also have the same issue here are my model properties

I have mailed you my model and labels can you please check subject should be yolo app crash

[surendramaran]

Sent your .pt file as well. This tflite throwed error when I tried to run in ultralytics environment.

On Tue, 23 Apr, 2024, 4:58 PM Himangshu Kalita, @.***> wrote:

It can detect 3 classes laptop, wallet and window class

On Mon, Apr 22, 2024 at 2:14 PM Surendra Maran @.***> wrote:

@HimangsKalita https://github.com/HimangsKalita How many classes your model can detect? by looking at the output it seems me 11, but your lebals.txt have 10 classes?

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[surendramaran]

It is in private mode now

[surendramaran]

Your model isn't yolov8, it is yolov5, this repository is only intended for Yolov8. I can't help you with that. Thanks

[HimangsKalita]

at. Th

My bad I trained for both yolov5 and yolov8, and mistakenly put yolov5 file in assets. This time I tried again with yolov8 file it is working great

The detection speed is slow maybe because I trained model with images 640X640 resolution I will train again in 320X320 it might help

[ZubairAhmad97]

how to inference this

[surendramaran]

Is it trained in Yolov8 ?

[ZubairAhmad97]

yes

[surendramaran]

Did you do anything different then usual to export? Please share with me your model.pt file

[ZubairAhmad97]

!yolo export model= '/content/gdrive/MyDrive/Drone/yolov8/new_file/yolov8s.pt' format='tflite' int8 imgsz = 256

my actual model is float32 but quantized it using above CLI for better speed

[surendramaran]

I have exported tflite with int8 many times, it is the first time I saw int8 input and output type. Thanks for reporting, I will make changes in my code to adapt int8 tflite.

Kindly also share the ultralytics version that you used.

[ZubairAhmad97]

[ZubairAhmad97]

I have exported tflite with int8 many times, it is the first time I saw int8 input and output type. Thanks for reporting, I will make changes in my code to adapt int8 tflite.

Kindly also share the ultralytics version that you used.

While exporting its generating multiple files among that file one fully quantized file is there whose input and output is int8

[surendramaran]

I understood now. Well try using that file in ultralytics environment. It won't there as well. the actual int8 quantized model is only best_int8.tflite

[surendramaran]

Oh wait it worked this time, I don't know why it didn't work before. I should look more into this.

[ZubairAhmad97]

Oh wait it worked this time, I don't know why it didn't work before. I should look more into this.

ok if you get any improvement in speed due to this please let me know

[cjs2000]

How to convert YOLOV8n.pt model to tflite format? I am using the official conversion method:

from ultralytics import YOLO model = YOLO(r'run\yolov8n\weights\best.pt') model.export(format="tflite",opset=13,batch=1)

But the converted model was placed in the assets folder, and then the Android program crashed