Comments (5)
I think it is related to dataset size..
from patchcore_anomaly_detection.
I think it is related to dataset size..
Do you mean it is related to the number of pictures in the training set?
So how much of dataset size is appropriate?
from patchcore_anomaly_detection.
Yes, It is related to the number of pictures.
I don't know about that. But I think you should do some experiment and find your own conditions.
from patchcore_anomaly_detection.
Okay, thanks, I'll try.
By the way,Is it reasonable to set the parameter N of the following code to a fixed value? Like the 50
PatchCore_anomaly_detection/train.py
Line 280 in 5680042
from patchcore_anomaly_detection.
I don't have deep insight about that. However, in my opinion, it depends on your dataset.
from patchcore_anomaly_detection.
Related Issues (20)
- Confusion matrix show error classifficating all the nominal (no defectives) sample HOT 1
- Error in test mode after faiss implementation HOT 5
- self.index.search(embedding_test, k=args.n_neighbors) kills the process HOT 1
- what's the difference between self(x) and self.model(x) in training_step
- How to apply SparseRandomProjector to large Image dataset?
- possible error in auroc computation step
- Attribute Error while running test
- heatmap accuracy?
- about number epoch HOT 1
- using pip install for faiss is not recommanded HOT 2
- wondering if the coreset sampling is only random sampling now
- the value of nearest neighbor size
- num_samples should be a positive integer value, but got num_samples=0 HOT 1
- how to run the train file on colab
- train error:ValueError: invalid literal for int() with base 10: HOT 2
- test HOT 1
- What is training on patchCore? (I think that patchCore does not have training phase) HOT 3
- Learning questions from a green beginner
- 缺陷检测交流群,相互交流一起进步 HOT 17
- the version of pytorch-lighting and torchmetrics
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from patchcore_anomaly_detection.