Updated readme to say correct pretrained network name

README.md

@@ -1,4 +1,8 @@
 # Eyeballer
+
+![Logo](/docs/eyeballer_logo.png)
+
+
 Give those screenshots of yours a quick eyeballing.
 
 Eyeballer is meant for large-scope network penetration tests where you need to find "interesting" targets from a huge set of web-based hosts. Go ahead and use your favorite screenshotting tool like normal (EyeWitness or GoWitness) and then run them through Eyeballer to tell you what's likely to contain vulnerabilities, and what isn't.
@@ -44,13 +48,13 @@ sudo pip3 install -r requirements-gpu.txt
 
 **Training Data** You can find our training data here:
 
-https://www.dropbox.com/sh/7aouywaid7xptpq/AAD_-I4hAHrDeiosDAQksnBma?dl=1
+https://www.dropbox.com/sh/usd03z9s0vnhzxu/AADyJvWgzlL1w4WnaAuxQbQQa?dl=1
 
 Pretty soon, we're going to add this as a TensorFlow DataSet, so you don't need to download this separately like this. It'll also let us version the data a bit better. But for now, just deal with it. There's two things you need from the training data:
 
 1. `images/` folder, containing all the screenshots (resized down to 224x140. We'll have the full-size images up soon)
 2. `labels.csv` that has all the labels
-3. `bishop-fox-pretrained-v1.h5` A pretrained weights file you can use right out of the box without training.
+3. `bishop-fox-pretrained-v2.h5` A pretrained weights file you can use right out of the box without training.
 
 Copy all three into the root of the Eyeballer code tree.