The Python application is now deployable from ground up

.gitignore

@@ -65,4 +65,12 @@ ehthumbs.db
 Thumbs.db
 
 # Swap files
-*.swp
+*.swp
+
+
+# Python3 Virtual Environment folders
+
+bin/
+lib/
+share/
+pyvenv.cfg

audio.py

@@ -42,9 +42,9 @@
 import re
 import sys
 
-from google.cloud import speech
-from google.cloud.speech import enums
-from google.cloud.speech import types
+#from google.cloud import speech
+#from google.cloud.speech import enums
+#from google.cloud.speech import types
 import pyaudio
 from six.moves import queue
 # [END import_libraries]
@@ -79,7 +79,7 @@ def __init__(self):
         except Exception as e:
             logging.info("Audio: input stream not available")
 
-        self._google_speech_client = speech.SpeechClient()
+        #self._google_speech_client = speech.SpeechClient()
 
     def exit(self):
         pass
@@ -201,32 +201,32 @@ def speech_recog(self, model):
                         logging.info("recog text: " + recog_text)
                         return recog_text
 
-    def speech_recog_google(self, locale):
-        config = types.RecognitionConfig(
-            encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
-            sample_rate_hertz=RATE,
-            language_code=locale)
-        streaming_config = types.StreamingRecognitionConfig(
-            config=config,
-            interim_results=False,
-            single_utterance=True)
-
-        t1 = time.time()
-        with self.stream_in as stream:
-            audio_generator = stream.generator()
-            requests = (types.StreamingRecognizeRequest(audio_content=content)
-                        for content in audio_generator)
-
-            responses = self._google_speech_client.streaming_recognize(streaming_config, requests)
+ #   def speech_recog_google(self, locale):
+ #       config = types.RecognitionConfig(
+ #           encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
+ #           sample_rate_hertz=RATE,
+ #           language_code=locale)
+ #       streaming_config = types.StreamingRecognitionConfig(
+ #           config=config,
+ #           interim_results=False,
+ #           single_utterance=True)
+#
+ #       t1 = time.time()
+  #      with self.stream_in as stream:
+   #         audio_generator = stream.generator()
+    #        requests = (types.StreamingRecognizeRequest(audio_content=content)
+     #                   for content in audio_generator)
+#
+ #           responses = self._google_speech_client.streaming_recognize(streaming_config, requests)
 
             # Now, put the transcription responses to use.
-            for response in responses:
-                if time.time() - t1 > 10:
-                    return ""
-                if response.results:
-                    result = response.results[0]
-                    if result.is_final:
-                        return result.alternatives[0].transcript
+  #          for response in responses:
+   #             if time.time() - t1 > 10:
+    #                return ""
+     #           if response.results:
+      #              result = response.results[0]
+       #             if result.is_final:
+        #                return result.alternatives[0].transcript
 
     class MicrophoneStream(object):
         """Opens a recording stream as a generator yielding the audio chunks."""

camera.py

@@ -85,11 +85,11 @@ def __init__(self):
                         self._photos.append({'name': filename})
             self.save_photo_metadata()
 
-        self._cnn_classifiers = {}
-        cnn_model = config.Config.get().get("cnn_default_model", "")
-        if cnn_model != "":
-            self._cnn_classifiers[cnn_model] = CNNManager.get_instance().load_model(cnn_model)
-            self._cnn_classifier_default = self._cnn_classifiers[cnn_model]
+        #self._cnn_classifiers = {}
+        #cnn_model = config.Config.get().get("cnn_default_model", "")
+        #if cnn_model != "":
+        #    self._cnn_classifiers[cnn_model] = CNNManager.get_instance().load_model(cnn_model)
+        #    self._cnn_classifier_default = self._cnn_classifiers[cnn_model]
 
         self._camera.grab_start()
         self._image_cv = self.get_image()

cv/image.py

@@ -34,7 +34,7 @@
 }
 
 try:
-    ocr = cv2.text.OCRTesseract_create("/usr/share/tesseract-ocr/", "eng", tesseract_whitelists['unspec'], 0, cv2.text.OCR_LEVEL_TEXTLINE)
+    ocr = cv2.text.OCRTesseract_create(Null, "eng", tesseract_whitelists['unspec'], 0, cv2.text.OCR_LEVEL_TEXTLINE)
 except:
     logging.info("tesseract not availabe")
 

main.py

@@ -47,7 +47,7 @@
 
 sh = logging.StreamHandler()
 # add a rotating handler
-fh = logging.handlers.RotatingFileHandler('/home/pi/coderbot/logs/coderbot.log', maxBytes=1000000, backupCount=5)
+fh = logging.handlers.RotatingFileHandler('./logs/coderbot.log', maxBytes=1000000, backupCount=5)
 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
 sh.setFormatter(formatter)
 fh.setFormatter(formatter)
@@ -92,8 +92,7 @@ def handle_home():
                            config=app.bot_config,
                            program_level=app.bot_config.get("prog_level", "std"),
                            cam=cam != None,
-                           cnn_model_names=json.dumps([[name] for name in cnn.get_models().keys()]))
-
+                           cnn_model_names = json.dumps({}))
 @app.route("/config", methods=["POST"])
 def handle_config():
     Config.write(request.form)
@@ -187,6 +186,21 @@ def video_stream(a_cam):
         yield frame
         yield "\r\n"
 
+@app.route("/video")
+def handle_video():
+    return """
+<html>
+<head>
+<style type=text/css>
+    body { background-image: url(/video/stream); background-repeat:no-repeat; background-position:center top; background-attachment:fixed; height:100% }
+</style>
+</head>
+<body>
+&nbsp;
+</body>
+</html>
+"""
+
 @app.route("/video/stream")
 def handle_video_stream():
     try:
@@ -198,6 +212,25 @@ def handle_video_stream():
     except:
         pass
 
+def video_stream_cv(a_cam):
+    while not app.shutdown_requested:
+        frame = a_cam.get_image_cv_jpeg()
+        yield ("--BOUNDARYSTRING\r\n" +
+               "Content-type: image/jpeg\r\n" +
+               "Content-Length: " + str(len(frame)) + "\r\n\r\n" +
+               frame + "\r\n")
+
+@app.route("/video/stream/cv")
+def handle_video_stream_cv():
+    try:
+        h = Headers()
+        h.add('Age', 0)
+        h.add('Cache-Control', 'no-cache, private')
+        h.add('Pragma', 'no-cache')
+        return Response(video_stream_cv(cam), headers=h, mimetype="multipart/x-mixed-replace; boundary=--BOUNDARYSTRING")
+    except:
+        pass
+
 @app.route("/photos", methods=["GET"])
 def handle_photos():
     logging.info("photos")
@@ -352,7 +385,7 @@ def run_server():
             except picamera.exc.PiCameraError:
                 logging.error("Camera not present")
 
-            cnn = CNNManager.get_instance()
+            #cnn = CNNManager.get_instance()
             event = EventManager.get_instance("coderbot")
             conv = Conversation.get_instance()
 

requirements.txt

@@ -0,0 +1,24 @@
+apiai==1.2.3
+Babel==2.5.3
+click==6.7
+Flask==1.0.2
+Flask-Babel==0.11.2
+Flask-Cors==3.0.4
+itsdangerous==0.24
+Jinja2==2.10
+MarkupSafe==1.0
+numpy==1.14.3
+opencv-contrib-python==3.4.0.12
+picamera==1.13
+pigpio==1.40.post1
+Pillow==5.1.0
+pkg-resources==0.0.0
+protobuf==3.0.0
+PyAudio==0.2.11
+pycairo==1.17.0
+Pypubsub==4.0.0
+pytz==2018.4
+six==1.11.0
+smbus2==0.2.0
+tensorflow==0.11.0
+Werkzeug==0.14.1