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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+00001.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,54 @@
+import gradio as gr
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+import os
+import pandas as pd
+
+model_gender = tf.keras.models.load_model('model_gender.h5')
+model_age = tf.keras.models.load_model('model_age.h5')
+
+actual_data = {
+    "000000.png": {"img": 1,"age": 85.0, "gender": "female"},
+    "000001.png": {"img": 2,"age": 72.0, "gender": "female"},
+    "000002.png": {"img": 3,"age": 45.0, "gender": "male"},
+    "000003.png": {"img": 4,"age": 59.0, "gender": "male"},
+    "000004.png": {"img": 5,"age": 37.0, "gender": "male"}
+    }
+
+df = pd.DataFrame(actual_data).T
+
+def preprocess_image(image):
+  # Assuming image is a PIL Image object from Gradio
+  img = image.convert('L')  # Convert to grayscale
+  img = img.resize((128, 128))
+  img = np.array(img) / 255.0  # Normalize pixel values
+  img = img.reshape((1, 128, 128, 1))  # Add channel dimension
+  return img
+
+def predict(image):
+  preprocessed_image = preprocess_image(image)
+  gender_pred = model_gender.predict(preprocessed_image)[0][0]
+  age_pred = model_age.predict(preprocessed_image)[0][0]
+  gender = "Male" if gender_pred > 0.5 else "Female"
+  list = "{:.2f}".format(age_pred),gender,df
+  return list
+
+
+
+# Gradio Interface with separate outputs
+text_age = gr.components.Textbox(label="Predicted Age")
+text_gender = gr.components.Textbox(label="Predicted Gender")
+
+interface = gr.Interface(predict, gr.components.Image(height=440,width=1000,label="Upload Image", type="pil"),
+                          outputs=[text_age, text_gender, gr.DataFrame(value=df)],
+                          examples=[
+                            os.path.join(os.path.dirname(__file__),"00000.png"),
+                            os.path.join(os.path.dirname(__file__),"00001.png"),
+                            os.path.join(os.path.dirname(__file__),"00002.png"),
+                            os.path.join(os.path.dirname(__file__),"00003.png"),
+                            os.path.join(os.path.dirname(__file__),"00004.png")],
+
+                          allow_flagging='never', 
+                          theme=gr.themes.Soft(),
+                          title="Age and Gender Prediction").launch()

model_age.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8cf2aeb631a124e81b75b704ad08c928aabb28bbbb1064859b3207bbeac6b965
+size 2556856

model_gender.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ebb54b7596daccca78a8e757c84b76a28b40b5d7da347e617850956877432a53
+size 2439608