Merge branch 'dev-it18141252' into 'master'

Dev it18141252

See merge request !8

README.md

@@ -13,9 +13,21 @@
 - .\env\Scripts\activate
 - uvicorn main:app --reload
 
-
 ## Export Dependencies
+
 - .\env\Scripts\activate
 - pip freeze > requirements.txt
 
-test change
+## Deploy to deta.sh
\ No newline at end of file
+
+- Install deta CLI
+
+  `iwr https://get.deta.dev/cli.ps1 -useb | iex`
+
+- Login to deta
+
+  `deta login`
+
+- Deploy
+
+  `deta new`

config/db.py

 from pymongo import MongoClient
-conn = MongoClient("mongodb+srv://skin-disease:skindis123@cluster0.bv8ia.mongodb.net/skinDiseaseDB?retryWrites=true&w=majority")
+conn = MongoClient("mongodb+srv://skin-disease:skindis123@cluster0.bv8ia.mongodb.net/skinDiseaseDB?retryWrites=true&w=majority", tls=True, tlsAllowInvalidCertificates=True)
+db = conn['skinDiseaseDB']
+disease_collection = db['disease']
 #mongodb+srv://skin-disease:skindis123@cluster0.bv8ia.mongodb.net/test
\ No newline at end of file

models/disease.py

 from pydantic import BaseModel
+from typing import Optional
 
 class Disease(BaseModel):
     name: str
-    description: str
+    description: Optional[str]=""
\ No newline at end of file

requirements.txt

 absl-py==0.14.0

routes/prediction.py

 from fastapi import APIRouter, File, UploadFile
+from pydantic import BaseModel
 import tensorflow as tf
 from tensorflow import keras 
 from typing import List
@@ -7,10 +8,15 @@ import pandas as pd
 import numpy as np
 import json
 from keras.preprocessing import image 
+from config.db import disease_collection
+from schemas.disease import diseasesEntity
 
 
 prediction = APIRouter()
 
+class Symptoms(BaseModel):
+    symptoms: List[int] 
+
 batch_size = 32
 img_height = 180
 img_width = 180
@@ -36,12 +42,13 @@ def read_imagefile( image:UploadFile ):
   return None
 
 
+# PREDICT DISEASE FROM SYMPTOMSES
 @prediction.post('/api/predictions/symptoms')
-async def predict_symptoms(symptoms: List[int]):
+async def predict_symptoms(symptoms: Symptoms):
     try:
         data = load_data_json('./data.json')
         threshold = 0.5
-        input = set(symptoms)
+        input = set(symptoms.symptoms)
         output = []
         for key in data.keys():
             numbers = [int(i) for i in key.split(',') if int(i) != 0]
@@ -49,12 +56,16 @@ async def predict_symptoms(symptoms: List[int]):
             score = len(list(input&set(numbers)))/lenght
             if score>=threshold:
                 output.append(data.get(key))
+        
+        diseases = diseasesEntity(disease_collection.find({"name": {"$in": output}})) 
                 
-        return {"success": True, "result": output}  
+        return {"success": True, "result": diseases}  
         
     except error: 
         return {"success": False, "msg": error}
 
+
+# PREDICT DISEASE FROM PICTURES
 @prediction.post('/api/predictions/picture')
 async def predict_symptoms(req_file: UploadFile = File(...)):
     try: