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Runtime error
| import numpy as np | |
| import cv2 | |
| from keras.models import load_model | |
| import gradio as gr | |
| model_info=load_model("GenderPredict_Model.h5",compile=True) | |
| def Gender_prediction(img,choice): | |
| value=-1 | |
| if(choice=="Through_Id_Card"): | |
| face_classifier = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml') | |
| scale_percent = 60 # percent of original size | |
| width = int(img.shape[1] * scale_percent / 100) | |
| height = int(img.shape[0] * scale_percent / 100) | |
| dim = (width, height) | |
| image = cv2.resize(img, dim, interpolation = cv2.INTER_AREA) | |
| gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
| faces = face_classifier.detectMultiScale(gray, 1.3, 5) | |
| if faces is (): | |
| print("No faces found") | |
| for (x, y, w, h) in faces: | |
| x = x - 25 # Padding trick to take the whole face not just Haarcascades points | |
| y = y - 40 # Same here... | |
| cv2.rectangle(image, (x, y), (x + w + 50, y + h + 70), (27, 200, 10), 2) | |
| for (x, y, width, height) in faces: | |
| roi = image[y:y+height, x:x+width] | |
| cv2.imwrite("face.jpg",roi) | |
| img=cv2.resize(cv2.imread("face.jpg"),(224,224)) | |
| result=model_info.predict(img.reshape(1,224,224,3)) | |
| value=result.argmax() | |
| elif(choice=="Through_Image"): | |
| img=cv2.resize(img,(224,224)) | |
| result=model_info.predict(img.reshape(1,224,224,3)) | |
| value=result.argmax() | |
| if(value==0): | |
| return "You are Female" | |
| elif(value==1): | |
| return "You are male" | |
| else: | |
| return "No Predict please Choose any option" | |
| interface=gr.Interface(fn=Gender_prediction,inputs=[gr.components.Image(label="Choose Image",type="numpy"),gr.components.Radio(['Through_Id_Card','Through_Image'],type="value",label="Select any One")], | |
| outputs=[gr.components.Textbox(label="Your Result")], | |
| examples=[ | |
| ["Girl_Id.jpg"], | |
| ["Male_id.jpg"], | |
| ["Female.jpg"], | |
| ["Men.jpg"] | |
| ]) | |
| interface.launch(debug=True) |