create initail app

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from tensorflow.keras.models import load_model
+from scipy.spatial import distance
+
+# Load model and haarcascade once
+model = load_model("D:\CV CEP\Mask_Detection\masknet.h5")
+face_cascade = cv2.CascadeClassifier("D:\CV CEP\Mask_Detection\haarcascade_frontalface_default.xml")
+
+mask_label = {0: 'MASK', 1: 'NO MASK'}
+dist_label = {0: (0, 255, 0), 1: (255, 0, 0)}
+MIN_DISTANCE = 75
+
+def predict(image):
+    img = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    orig_img = img.copy()
+
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(gray, 1.1, 4)
+
+    label = [0 for _ in range(len(faces))]
+
+    if len(faces) >= 2:
+        centers = [(x + w // 2, y + h // 2) for (x, y, w, h) in faces]
+        for i in range(len(centers) - 1):
+            for j in range(i + 1, len(centers)):
+                dist = distance.euclidean(centers[i], centers[j])
+                if dist < MIN_DISTANCE:
+                    label[i] = 1
+                    label[j] = 1
+
+    for i in range(len(faces)):
+        (x, y, w, h) = faces[i]
+        face_crop = img[y:y + h, x:x + w]
+        face_crop = cv2.resize(face_crop, (128, 128))
+        face_crop = np.reshape(face_crop, [1, 128, 128, 3]) / 255.0
+
+        result = model.predict(face_crop)
+        class_id = np.argmax(result)
+
+        cv2.rectangle(orig_img, (x, y), (x + w, y + h), dist_label[label[i]], 2)
+        cv2.putText(orig_img, mask_label[class_id], (x, y - 10),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.7, dist_label[label[i]], 2)
+
+    output = cv2.cvtColor(orig_img, cv2.COLOR_BGR2RGB)
+    return output
+
+iface = gr.Interface(fn=predict, inputs=gr.Image(type="numpy"), outputs="image", title="Face Mask Detection")
+iface.launch()

masknet.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:95c32b3bc83e191312b6f003bdf0d54f5cf94d44aed9a6fd4d45d88d2183595e
+size 80362728

requirements.txt

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+gradio
+tensorflow
+opencv-python-headless
+numpy
+scipy
+matplotlib