Revert "update README.md with installation instructions for TensorFlo…

…w 2.2 (#27)" (#29)

This reverts commit 87b23cb.

README.md

@@ -40,68 +40,23 @@ Before you get started, you should have an up-to-date installation of Raspbian 1
 1. Install system dependencies
 
 ```bash
-$ sudo apt-get update && sudo apt-get install -y \
+sudo apt-get update && sudo apt-get install -y \
     cmake python3-dev libjpeg-dev libatlas-base-dev raspi-gpio libhdf5-dev python3-smbus
 ```
 
-1. Create new virtual environment
+2. Install TensorFlow 2.0 (community-built wheel)
 
 ```bash
-$ python3 -m venv .venv
-```
-
-3. Activate virtual environment
-
-```bash
-$ source .venv/bin/activate
-```
-
-4. Upgrade setuptools
-
-```bash
-$ pip install --upgrade setuptools
-```
-
-5. Install TensorFlow 2.2 (community-built wheel)
-
-```bash
-$ pip install https://github.com/leigh-johnson/Tensorflow-bin/releases/download/v2.2.0/tensorflow-2.2.0-cp37-cp37m-linux_armv7l.whl
+pip install https://github.com/leigh-johnson/Tensorflow-bin/blob/master/tensorflow-2.0.0-cp37-cp37m-linux_armv7l.whl?raw=true
 
 ```
 
-6. Install the `rpi-deep-pantilt` package.
+3. Install the `rpi-deep-pantilt` package.
 
 ```bash
 pip install rpi-deep-pantilt
 ```
 
-=======
-# Configuration
-
-WARNING: Do not skip this section! You will not be able to use `rpi-deep-pantilt` without properly configuring your Pi.
-
-### Enable Pi Camera
-
-1. Run `sudo raspi-config` and select `Interfacing Options` from the Raspberry Pi Software Configuration Tool’s main menu. Press ENTER.
-
-![raspi-config main menu](/images/camera1.png)
-
-2. Select the Enable Camera menu option and press ENTER.
-
-![raspi-config interfacing options menu](/images/camera2.png)
-
-3. In the next menu, use the right arrow key to highlight ENABLE and press ENTER.
-
-![raspi-config enable camera yes/no menu](/images/camera3.png)
-
-### Enable i2c in Device Tree
-
-1. Open `/boot/config.txt` and verify the following `dtparams` lines are uncommented:
-
-```bash
-dtparam=i2c1=on
-dtparam=i2c_arm=on
-```
 # Example Usage
 
 ## Object Detection
@@ -218,25 +173,6 @@ I was able to use the same model architechture for FLOAT32 and UINT8 input, `fac
 
 This model is derived from `facessd_mobilenet_v2_quantized_320x320_open_image_v4` in [tensorflow/models](https://github.com/tensorflow/models). 
 
-# Common Issues
-
-### i2c is not enabled
-
-If you run `$ rpi-deep-pantilt test pantilt` and see a similar error, check your Device Tree configuration.
-
-```python
-File "/home/pi/projects/rpi-deep-pantilt/.venv/lib/python3.7/site-packages/pantilthat/pantilt.py", line 72, in setup
-self._i2c = SMBus(1)
-FileNotFoundError: [Errno 2] No such file or directory
-```
-
-Open `/boot/config.txt` and ensure the following lines are uncommented:
-
-```bash
-dtparam=i2c1=on
-dtparam=i2c_arm=on
-```
-
 # Credits
 
 The MobileNetV3-SSD model in this package was derived from [TensorFlow's model zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md), with [post-processing ops added](https://gist.github.com/leigh-johnson/155264e343402c761c03bc0640074d8c).
@@ -247,4 +183,3 @@ This package was created with
 [Cookiecutter](https://github.com/audreyr/cookiecutter) and the
 [audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage)
 project template.
-

setup.py

@@ -22,10 +22,10 @@
     'Click>=7.0',
     'pillow',
     'h5py',
-    'tensorflow>=2.2.0'
 ]
 
 trainer_requirements = [
+    'tensorflow==2.0.0',
     'numpy'
 ]