Minor typo edit

Author: EdjeElectronics

README.md

@@ -50,7 +50,6 @@ This portion of the tutorial goes over the full set up required. It is fairly me
 Create a folder directly in C: and name it “tensorflow1”. This working directory will contain the full TensorFlow object detection framework, as well as your training images, training data, trained classifier, configuration files, and everything else needed for the object detection classifier.
 
 Download the full TensorFlow object detection repository located at https://github.com/tensorflow/models by clicking the “Clone or Download” button and downloading the zip file. Open the downloaded zip file and extract the “models-master” folder directly into the C:\tensorflow1 directory you just created. Rename “models-master” to just “models”.
-
 (Note, this tutorial was done using this [GitHub commit](https://github.com/tensorflow/models/tree/079d67d9a0b3407e8d074a200780f3835413ef99) of the TensorFlow Object Detection API. If portions of this tutorial do not work, it may be necessary to download and use this exact commit rather than the most up-to-date version.)
 
 #### 2b. Download the Faster-RCNN-Inception-V2-COCO model from TensorFlow's model zoo
@@ -73,7 +72,7 @@ At this point, here is what your \object_detection folder should look like:
   <img src="doc/object_detection_directory.jpg">
 </p>
 
-This repository contains the images, annotation data, .csv files, and TFRecords needed to train a "Pinochle Deck" playing card detector. You can use these images and data to practice making your own Pinochle Card Detector. It also contains Python scripts that are used to generate the training data, as well as test to test out the object detection classifier on images, videos, or a webcam feed. You can ignore the \doc folder and its files; they are just there to hold the images used for this readme.
+This repository contains the images, annotation data, .csv files, and TFRecords needed to train a "Pinochle Deck" playing card detector. You can use these images and data to practice making your own Pinochle Card Detector. It also contains Python scripts that are used to generate the training data. It has scripts to test out the object detection classifier on images, videos, or a webcam feed. You can ignore the \doc folder and its files; they are just there to hold the images used for this readme.
 
 If you want to practice training your own "Pinochle Deck" card detector, you can leave all the files as they are. You can follow along with this tutorial to see how each of the files were generated, and then run the training. You will still need to generate the TFRecord files (train.record and test.record) as described in Step 4.