Added basic test model

.gitignore

@@ -0,0 +1,2 @@
+unitylog.txt
+env

DQN_model.py

@@ -0,0 +1,32 @@
+import os
+import gym
+import gym_donkeycar
+import numpy as np
+from stable_baselines.common.vec_env import DummyVecEnv
+from stable_baselines.ddpg.policies import CnnPolicy
+from stable_baselines import DDPG
+
+#SET UP ENVIRONMENT
+os.environ['DONKEY_SIM_PATH'] = f"../DonkeySimMac/donkey_sim.app/Contents/MacOS/donkey_sim"
+os.environ['DONKEY_SIM_PORT'] = str(9091)
+os.environ['DONKEY_SIM_HEADLESS'] = str(0) # "1" is headless
+
+env = gym.make("donkey-warehouse-v0")
+#gym.make("donkey-generated-roads-v0")
+
+timesteps = 100000 # Set this to a reasonable number
+model_name = "ddpg_model" # Change the model name to your preferences
+training = True # Change this to test or use the model
+
+if training:
+    vec_env = DummyVecEnv([lambda: env])
+    model = DDPG(CnnPolicy, vec_env, verbose=1)
+    model.learn(total_timesteps=timesteps)
+    model.save(model_name)
+else:
+    model = DDPG.load(model_name)
+    obv = env.reset()
+    for t in range(10000):
+        action, _states = model.predict(obv) # drive straight with small speed
+    # execute the action
+        obv, reward, done, info = env.step(action)

README.md

@@ -55,6 +55,7 @@ https://github.com/tawnkramer/gym-donkeycar/tree/master/examples
 Download program for your computer:
 https://github.com/tawnkramer/gym-donkeycar/releases
 
+```
 import os
 import gym
 import gym_donkeycar
@@ -73,3 +74,5 @@ for t in range(100):
     action = np.array([0.0,0.5]) # drive straight with small speed
 # execute the action
 obv, reward, done, info = env.step(action)
+
+```