Merge pull request #125 from sanyatuning/policy

Restructure policy dir, create python package openbot

policy/openbot/__init__.py

@@ -0,0 +1,7 @@
+import os
+
+base_dir = os.path.dirname(os.path.dirname(__file__))
+dataset_dir = os.path.join(base_dir, "dataset")
+
+if not (os.path.exists(dataset_dir)):
+    os.makedirs(dataset_dir)

policy/server/README.md → policy/openbot/server/README.md

@@ -8,30 +8,29 @@ If you do not want install the dependencies globally, activate your conda enviro
 conda activate openbot
 ```
 
-Make sure you are in the folder `policy/server`. Now, you can install all the dependencies with the following command:
+Make sure you are in the folder `policy`. Now, you can install all the dependencies with the following command:
 
 ```
-pip install -r requirements.txt
+pip install -r openbot/server/requirements.txt
 ```
 
 ## Running the server
 
 You can run the python server with the command:
 
 ```
-python main.py
+python -m openbot.server
 ```
 
 There is also a developer mode:
 
 ```
-adev runserver main.py
+adev runserver openbot/server
 ```
 
 When you run the server you should see something like:
 
 ```
-Dataset dir: <clone-dir>/OpenBot/policy/dataset
 Skip address 127.0.0.1 @ interface lo0
 Found address 192.168.x.x @ interface en0
 Registration of a service, press Ctrl-C to exit...
@@ -45,7 +44,7 @@ You can now open your browser to visualize the dataset and see incoming uploads
 http://localhost:8000/uploaded/
 ```
 
-<img src="../../docs/images/server.gif" width="100%" alt="server" />
+<img src="../../../docs/images/server.gif" width="100%" alt="server" />
 
 ## Troubleshooting
 

policy/openbot/server/__main__.py

@@ -0,0 +1,5 @@
+from aiohttp import web
+from openbot.server.main import app
+
+if __name__ == '__main__':
+    web.run_app(app, port=8000)

policy/server/openbot/api.py → policy/openbot/server/api.py

@@ -3,7 +3,7 @@
 
 from aiohttp import web
 
-from . import dataset_dir
+from .. import dataset_dir
 
 
 async def handle_api(request):

policy/server/main.py → policy/openbot/server/main.py

@@ -3,13 +3,10 @@
 from aiohttp import web
 import aiohttp_jinja2
 import jinja2
-from openbot.api import dataset_dir, handle_api, get_dir_info
-from openbot.preview import handle_preview
-from openbot.upload import handle_file_upload
-from openbot.zeroconf import register
-
-
-print("Dataset dir: " + dataset_dir)
+from .api import dataset_dir, handle_api, get_dir_info
+from .preview import handle_preview
+from .upload import handle_file_upload
+from .zeroconf import register
 
 
 @aiohttp_jinja2.template("index.html")
@@ -40,7 +37,5 @@ async def handle_post(request: web.Request) -> web.Response:
 ])
 app.on_startup.append(register)
 aiohttp_jinja2.setup(
-    app, loader=jinja2.FileSystemLoader(os.path.join(os.getcwd(), "templates"))
+    app, loader=jinja2.FileSystemLoader(os.path.join(os.path.dirname(__file__), "templates"))
 )
-if __name__ == '__main__':
-    web.run_app(app, port=8000)

policy/server/openbot/preview.py → policy/openbot/server/preview.py

@@ -4,7 +4,7 @@
 from aiohttp import web
 import imageio
 
-from . import dataset_dir
+from .. import dataset_dir
 
 
 async def handle_preview(request):

policy/server/openbot/upload.py → policy/openbot/server/upload.py

@@ -4,7 +4,7 @@
 
 from aiohttp import multipart, web
 
-from . import dataset_dir
+from .. import dataset_dir
 
 
 async def handle_file_upload(field: multipart.BodyPartReader) -> web.Response:

policy/utils.py → policy/openbot/utils.py

@@ -8,7 +8,6 @@
 from nbconvert import HTMLExporter
 import codecs
 import nbformat
-import metrics
 
 def save_notebook():
     Javascript("IPython.notebook.save_notebook()")
@@ -51,7 +50,7 @@ def show_train_batch(image_batch, cmd_batch, label_batch,fig_num=1):
       plt.imshow(image_batch[n])
       plt.title("Cmd: %s, Label: [%.2f %.2f]" \
         %(cmd_batch[n],float(label_batch[n][0]),float(label_batch[n][1])))
-      plt.axis('off')  
+      plt.axis('off')
 
 def show_test_batch(image_batch, cmd_batch, label_batch, pred_batch,fig_num=1):
   plt.figure(num=fig_num,figsize=(15,10))
@@ -60,7 +59,7 @@ def show_test_batch(image_batch, cmd_batch, label_batch, pred_batch,fig_num=1):
       plt.imshow(image_batch[n])
       plt.title("Cmd: %s, Label: [%.2f %.2f], Pred: [%.2f %.2f]" \
         %(cmd_batch[n],float(label_batch[n][0]),float(label_batch[n][1]),float(pred_batch[n][0]),float(pred_batch[n][1])))
-      plt.axis('off')  
+      plt.axis('off')
 
 def generate_tflite(path, filename):
     converter = tf.lite.TFLiteConverter.from_saved_model(os.path.join(path, filename))
@@ -69,14 +68,14 @@ def generate_tflite(path, filename):
     return tflite_model
 
 def save_tflite(tflite_model, path, filename):
-    open(os.path.join(path, filename + ".tflite"), "wb").write(tflite_model)    
+    open(os.path.join(path, filename + ".tflite"), "wb").write(tflite_model)
 
 def load_model(model_path,loss_fn,metric_list):
     model = tf.keras.models.load_model(model_path,
     custom_objects=None,
     compile=False
     )
-    model.compile(loss=loss_fn, 
+    model.compile(loss=loss_fn,
                   metrics=metric_list)
     return model
 
@@ -102,7 +101,7 @@ def compare_tf_tflite(model, tflite_model,img=None,cmd=None):
             input_data[input_detail['name']] = (np.array(np.random.random_sample(input_detail['shape']), dtype=np.float32))
         interpreter.set_tensor(input_detail['index'], input_data[input_detail['name']])
 
-    
+
     interpreter.invoke()
 
     # The function `get_tensor()` returns a copy of the tensor data.
@@ -117,4 +116,4 @@ def compare_tf_tflite(model, tflite_model,img=None,cmd=None):
     # Compare the result.
     for tf_result, tflite_result in zip(tf_results, tflite_results):
       print("Almost equal (5% tolerance):", np.allclose(tf_result, tflite_result, rtol=5e-02))
-      #np.testing.assert_almost_equal(tf_result, tflite_result, decimal=2)
+      #np.testing.assert_almost_equal(tf_result, tflite_result, decimal=2)

policy/policy_learning.ipynb

@@ -64,8 +64,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import utils\n",
-    "import dataloader"
+    "from openbot import dataloader, utils"
    ]
   },
   {
@@ -172,7 +171,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import associate_frames\n",
+    "from openbot import associate_frames\n",
     "max_offset = 1e3 #1ms\n",
     "train_frames = associate_frames.match_frame_ctrl_cmd(train_data_dir, \n",
     "                                                     train_datasets, \n",
@@ -602,10 +601,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import models\n",
-    "import losses\n",
-    "import metrics\n",
-    "import callbacks\n",
+    "from openbot import callbacks, losses, metrics, models\n",
     "\n",
     "model = models.cil_mobile(NETWORK_IMG_WIDTH,NETWORK_IMG_HEIGHT,BN)\n",
     "loss_fn = losses.sq_weighted_mse_angle \n",