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app.py
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app.py
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from flask import Flask, render_template, request
# from keras.models import load_model
# from keras.preprocessing import image
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import os
import cv2
import tensorflow as tf
from tensorflow import keras
import joblib
app = Flask(__name__)
model= keras.models.load_model(r"./model")
label_encoder = joblib.load(r"./label_encoder.joblib")
# routes
@app.route("/", methods=['GET', 'POST'])
def main():
return render_template("index.html")
@app.route("/submit", methods=['GET', 'POST'])
def get_output():
if request.method == 'POST':
# img = request.files['my_image']
# img_path = "static/" + img.filename
# img.save(img_path)
# if(request.region_selected == "region 1"):
# img_path = "model/All_Regions/Region 1/" + img.filename
# img.save(img_path)
# else:
# img_path = "model/All_Regions/Region 2/" + img.filename
# img.save(img_path)
All_Region_dir = request.form['add_info']
finaldf=pd.DataFrame(columns=['Image_Name','Region_Name','Species'])
for i in range(0,len(os.listdir(All_Region_dir))):
region_dir=All_Region_dir+'\\'+os.listdir(All_Region_dir)[i]
preds=animal_identifier(region_dir)
finaldf=finaldf.append(preds,ignore_index=True)
finaldf.to_csv('Region_Wise_Predictions.csv',index=False)
# p = predict_label(img_path)
# render_template("index.html", prediction = p, img_path = img_path)
return render_template("submit.html", message = All_Region_dir)
def animal_identifier(region_dir):
df=pd.DataFrame(columns=['Image_Name','Region_Name','Species'])
for i in range(0,len(os.listdir(region_dir))):
images=[]
img = cv2.imread(region_dir+'/'+os.listdir(region_dir)[i])
resized_img = cv2.resize(img,(224,224))
resized_img = resized_img / 255.0
images.append(resized_img)
images = np.array(images,dtype = 'float32')
preds = model.predict(images)
preds = np.argmax(preds,axis = 1)
pred_animal=label_encoder.inverse_transform([preds[0]])[0]
df.loc[i,'Image_Name']=os.listdir(region_dir)[i]
df.loc[i,'Region_Name']=region_dir.split('\\')[-1]
df.loc[i,'Species']=pred_animal
return df
if __name__ == '__main__':
#app.debug = True
app.run(debug=True)