Merge branch 'master' of https://github.com/matthewearl/deep-anpr

README.md

@@ -4,6 +4,14 @@ Using neural networks to build an automatic number plate recognition system.
 See [this blog post](http://matthewearl.github.io/2016/05/06/cnn-anpr/) for an
 explanation.
 
+**Note: This is an experimental project and is incomplete in a number of ways,
+if you're looking for a practical number plate recognition system this project
+is not for you.** If however you've read the above blog post and wish to tinker
+with the code, read on.  If you're really keen you can tackle some of the
+enhancements on the Issues page to help make this project more practical.
+Please comment on the relevant issue if you plan on making an enhancement and
+we can talk through the potential solution.
+
 Usage is as follows:
 
 1. `./extractbgs.py SUN397.tar.gz`: Extract ~3GB of background images from the [SUN database](http://groups.csail.mit.edu/vision/SUN/)
@@ -14,7 +22,10 @@ Usage is as follows:
     already exist.) This step requires `UKNumberPlate.ttf` to be in the current
     directory, which can be [downloaded here](http://www.dafont.com/uk-number-plate.font).
 
-3. `./train.py`: Train the model. A GPU is recommended for this step.
+3. `./train.py`: Train the model. A GPU is recommended for this step. It will
+   take around 100,000 batches to converge. When you're satisfied that the
+   network has learned enough press `Ctrl+C` and the process will write the
+   weights to `weights.npz` and return.
 
 4. `./detect.py in.jpg weights.npz out.jpg`: Detect number plates in an image.