avancement rapport

code/backend_reconnaissance/.dockerignore

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+**/__pycache__
+**/.venv
+**/.classpath
+**/.dockerignore
+**/.env
+**/.git
+**/.gitignore
+**/.project
+**/.settings
+**/.toolstarget
+**/.vs
+**/.vscode
+**/*.*proj.user
+**/*.dbmdl
+**/*.jfm
+**/bin
+**/charts
+**/docker-compose*
+**/compose*
+**/Dockerfile*
+**/node_modules
+**/npm-debug.log
+**/obj
+**/secrets.dev.yaml
+**/values.dev.yaml
+LICENSE
+README.md

code/backend_reconnaissance/Dockerfile

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+FROM python:3.8-slim
+
+#Ne pas créer les fichiers .pyc
+ENV PYTHONDONTWRITEBYTECODE=1
+#Afficher les logs directement dans le terminal
+ENV PYTHONUNBUFFERED=1
+
+#Installation des dépendances de opencv (TODO: supprimer si plus besoin)
+RUN apt-get update
+RUN apt-get install ffmpeg libsm6 libxext6  -y
+
+# Installation des dépendances python
+COPY requirements.txt .
+RUN python -m pip install -r requirements.txt
+
+# Création du répertoire de travail
+WORKDIR /app
+COPY . /app
+
+CMD ["python", "main.py"]

code/backend_reconnaissance/exemple_utilisation.py

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+import requests
+#Exemple ajout d'un commentaire depuis la borne (site ou geste)
+avis = {
+    "note": 8,
+    "source": "borne",
+    #Optionel
+    "auteur_age": 20,
+    "notes_autre": '{"proprete":8,"calme":10}',
+    "auteur_sexe": 'f',
+    "commentaire": "Commentaire"
+}
+
+# res = requests.post("http://localhost:8080/add_review", data=avis)
+# print(res.text)
+
+#Exemple ajout d'un commentaire trouvé sur les réseaux sociaux
+avis = {
+    "auteur_nom": "michel",
+    "source": "instagram",
+    "note": 8,
+    "date": "2022-12-24",
+    #Optionel
+    "commentaire": "J'ai beaucoup aimé !",
+    "lien": "https://instagram.com/si_insta_avait_des_liens_vers_des_commentaires_faudrait_le_mettre_ici",
+    "auteur_lien": "https://instagram.com/michel",
+}
+
+res = requests.post("http://localhost:8080/add_social_review", data=avis)
+print(res.text)

code/backend_reconnaissance/hands.py

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+import cv2
+import mediapipe as mp
+mp_drawing = mp.solutions.drawing_utils
+mp_drawing_styles = mp.solutions.drawing_styles
+mp_hands = mp.solutions.hands
+
+# For webcam input:
+cap = cv2.VideoCapture(0)
+hands = mp_hands.Hands(
+    model_complexity=0,
+    min_detection_confidence=0.5,
+    min_tracking_confidence=0.5)
+
+def frame():
+  if cap.isOpened():
+    success, image = cap.read()
+    if not success:
+      print("Ignoring empty camera frame.")
+      # If loading a video, use 'break' instead of 'continue'.
+      return
+
+    # To improve performance, optionally mark the image as not writeable to
+    # pass by reference.
+    image.flags.writeable = False
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    results = hands.process(image)
+
+    # Draw the hand annotations on the image.
+    image.flags.writeable = True
+    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    if results.multi_hand_landmarks:
+      for hand_landmarks in results.multi_hand_landmarks:
+        mp_drawing.draw_landmarks(
+            image,
+            hand_landmarks,
+            mp_hands.HAND_CONNECTIONS,
+            mp_drawing_styles.get_default_hand_landmarks_style(),
+            mp_drawing_styles.get_default_hand_connections_style())
+    # Flip the image horizontally for a selfie-view display.
+    # cv2.imshow('MediaPipe Hands', cv2.flip(image, 1))
+    if cv2.waitKey(5) & 0xFF == 27:
+      return
+# cap.release()
+

code/backend_reconnaissance/main.py

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+import asyncio
+import json
+import websockets
+import random
+import os
+import hands
+import time
+
+
+class WebsocketServer:
+    def __init__(self,getEffects,port=os.getenv("PORT"),host=os.getenv("HOST")) -> None:
+        self.host = host
+        self.port = port
+        self.getEffects = getEffects
+    
+    async def run(self):
+        async with websockets.serve(self.handler, self.host, self.port):
+            await asyncio.Future()
+
+
+    async def handler(self,websocket):
+        while True:
+            messages = self.getEffects()
+            hands.frame()
+            await websocket.send(json.dumps(messages))
+            await asyncio.sleep(1/30)
+
+#Remplacer ça par la fonction qui récupère les effets (dans le module de reconnaissance de gestes)
+def getEffects():
+    return {"type": "effects", "effects": [{"type": "thumbs_up", "x":random.randint(0,100), "y": random.randint(0,100), "width": 50, "height": 50}]}
+
+server = WebsocketServer(getEffects)
+asyncio.run(server.run())

code/backend_reconnaissance/requirements.txt

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+websockets
+requests
+opencv-python
+mediapipe