Spaces:
Runtime error
Runtime error
from keras.models import load_model | |
from PIL import Image | |
import numpy as np | |
import cv2 | |
#the following are to do with this interactive notebook code | |
from matplotlib import pyplot as plt # this lets you draw inline pictures in the notebooks | |
import pylab # this allows you to control figure size | |
pylab.rcParams['figure.figsize'] = (10.0, 8.0) # this controls figure size in the notebook | |
###loading model### | |
age_model = load_model('age_model_pretrained.h5') | |
gender_model = load_model('gender_model_pretrained.h5') | |
emotion_model = load_model('emotion_model_pretrained.h5') | |
# Labels on Age, Gender and Emotion to be predicted | |
age_ranges = ['1-5', '6-10', '11-15', '16-20', '21-25', '26-30', '31-35','36-40','41-50','51-60','61-70','71-80','81-90'] | |
gender_ranges = ['male', 'female'] | |
emotion_ranges= ['positive','negative','neutral'] | |
############################ | |
import io | |
import streamlit as st | |
bytes_data=None | |
img_file_buffer=st.camera_input("Take a picture") | |
if img_file_buffer is not None: | |
test_image = Image.open(img_file_buffer) | |
st.image(test_image, use_column_width=True) | |
st.write(type(test_image)) | |
test_image = np.asarray(test_image) | |
gray = cv2.cvtColor(test_image,cv2.COLOR_BGR2GRAY) | |
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') | |
faces = face_cascade.detectMultiScale(gray, 1.3, 5) | |
i = 0 | |
for (x,y,w,h) in faces: | |
i = i+1 | |
cv2.rectangle(test_image,(x,y),(x+w,y+h),(203,12,255),2) | |
img_gray=gray[y:y+h,x:x+w] | |
emotion_img = cv2.resize(img_gray, (48, 48), interpolation = cv2.INTER_AREA) | |
emotion_image_array = np.array(emotion_img) | |
emotion_input = np.expand_dims(emotion_image_array, axis=0) | |
output_emotion= emotion_ranges[np.argmax(emotion_model.predict(emotion_input))] | |
gender_img = cv2.resize(img_gray, (100, 100), interpolation = cv2.INTER_AREA) | |
gender_image_array = np.array(gender_img) | |
gender_input = np.expand_dims(gender_image_array, axis=0) | |
output_gender=gender_ranges[np.argmax(gender_model.predict(gender_input))] | |
age_image=cv2.resize(img_gray, (200, 200), interpolation = cv2.INTER_AREA) | |
age_input = age_image.reshape(-1, 200, 200, 1) | |
output_age = age_ranges[np.argmax(age_model.predict(age_input))] | |
output_str = str(i) + ": "+ output_gender + ', '+ output_age + ', '+ output_emotion | |
st.write(output_str) | |
col = (0,255,0) | |
cv2.putText(test_image, str(i),(x,y),cv2.FONT_HERSHEY_SIMPLEX,1,col,2) | |
st.image(cv2.cvtColor(test_image, cv2.COLOR_BGR2RGB)) | |
if bytes_data is None: | |
st.stop() | |