Comments (8)
No I did not - still have errors. Important difference can be that the FastAI example includes Training and Validation data which I wouldn't want to load for an Inference use case. I plan to spend more time on this issue this week. I will share the solution if I get it working. Please do the same.
from objectdetection.
Please take a look at FastAI and how to perform inference on a single image.
from objectdetection.
Please take a look at FastAI and how to perform inference on a single image.
I looked there. It did not work.
Did you manage to make it work for inference yourself?
from objectdetection.
Work on it
from objectdetection.
Moin,
please take a look at this example:
https://colab.research.google.com/drive/16un8u65D4oTWiWzpdjMU_cpnVasaQ72n#scrollTo=TY_S_53Pikjt -> Inference example
from objectdetection.
Predictions are very different from show_results_side_by_side
from objectdetection.
You have to Normalize your input data.
Uncomment:
#image = transforms.Normalize(mean, std)(image)
from objectdetection.
Works. But I retrained my model without normalization
from objectdetection.
Related Issues (20)
- No module name BoundingBox HOT 1
- size problem
- Fastai V2
- Anchors are totally wrong HOT 2
- In examples, incorrect anchors preview
- Exception: It's not possible to apply those transforms to your dataset HOT 5
- Validation scores
- Prediction Example HOT 2
- Index Error when using Transfer Learning HOT 1
- Migrating ObjectDetection to FastAIv2 HOT 2
- Error in NMS function
- any script to get prediction on single .scn file with coco .json annotations
- How to change number of classes for already trained retinanet model HOT 3
- How can i get the predicted classes from my retinanet model detection over the images.
- How to use fastai v2 for this library HOT 1
- How to save the image patches that are created from databunch method?
- Requesting object detection for fastai v2 HOT 1
- mAP seems to be [email protected] not mAP value
- Any script to train the model ? HOT 4
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from objectdetection.