Create app.py

app.py

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+import io
+import gradio as gr
+from PIL import Image, ImageDraw, ImageFont
+
+from azure.ai.vision.face import FaceClient
+from azure.ai.vision.face.models import (
+    FaceDetectionModel,
+    FaceRecognitionModel,
+    FaceAttributeTypeDetection01,
+)
+from azure.core.credentials import AzureKeyCredential
+
+# ✅ Hardcoded endpoint (safe to keep in code)
+AI_SERVICE_ENDPOINT = "https://face59137214.cognitiveservices.azure.com/"
+
+
+def pil_to_bytes(img: Image.Image) -> bytes:
+    if img.mode != "RGB":
+        img = img.convert("RGB")
+    buf = io.BytesIO()
+    img.save(buf, format="JPEG", quality=95)
+    return buf.getvalue()
+
+
+def analyze_and_annotate(image: Image.Image, api_key: str):
+    if image is None:
+        return "No image provided.", None
+
+    if not api_key or not api_key.strip():
+        return "Please paste your AI_SERVICE_KEY in the box.", image
+
+    # Create Face client using hardcoded endpoint + user-pasted key
+    face_client = FaceClient(
+        endpoint=AI_SERVICE_ENDPOINT,
+        credential=AzureKeyCredential(api_key.strip())
+    )
+
+    # Facial features to retrieve (same as the lab)
+    features = [
+        FaceAttributeTypeDetection01.HEAD_POSE,
+        FaceAttributeTypeDetection01.OCCLUSION,
+        FaceAttributeTypeDetection01.ACCESSORIES,
+    ]
+
+    img_bytes = pil_to_bytes(image)
+
+    detected_faces = face_client.detect(
+        image_content=img_bytes,
+        detection_model=FaceDetectionModel.DETECTION01,
+        recognition_model=FaceRecognitionModel.RECOGNITION01,
+        return_face_id=False,
+        return_face_attributes=features,
+    )
+
+    if not detected_faces:
+        return "0 faces detected.", image
+
+    # Prepare annotation image
+    annotated = image.copy()
+    if annotated.mode != "RGB":
+        annotated = annotated.convert("RGB")
+    draw = ImageDraw.Draw(annotated)
+
+    # Font (best-effort)
+    try:
+        font = ImageFont.truetype("arial.ttf", 24)
+    except Exception:
+        font = ImageFont.load_default()
+
+    lines = [f"{len(detected_faces)} faces detected.\n"]
+
+    for idx, face in enumerate(detected_faces, start=1):
+        r = face.face_rectangle
+        left, top, right, bottom = r.left, r.top, r.left + r.width, r.top + r.height
+
+        # Bounding box + face number label
+        draw.rectangle([(left, top), (right, bottom)], outline="lime", width=5)
+
+        label = str(idx)
+        x0, y0, x1, y1 = draw.textbbox((0, 0), label, font=font)
+        tw, th = x1 - x0, y1 - y0
+        pad = 6
+        label_bg = [(left, max(0, top - th - 2 * pad)), (left + tw + 2 * pad, top)]
+        draw.rectangle(label_bg, fill="lime")
+        draw.text((left + pad, label_bg[0][1] + pad), label, fill="black", font=font)
+
+        # Extract attributes
+        attrs = face.face_attributes
+        hp = getattr(attrs, "head_pose", None)
+        occ = getattr(attrs, "occlusion", None)
+        acc = getattr(attrs, "accessories", None)
+
+        yaw = getattr(hp, "yaw", None) if hp else None
+        pitch = getattr(hp, "pitch", None) if hp else None
+        roll = getattr(hp, "roll", None) if hp else None
+
+        forehead_occ = occ.get("foreheadOccluded") if isinstance(occ, dict) else None
+        eye_occ = occ.get("eyeOccluded") if isinstance(occ, dict) else None
+        mouth_occ = occ.get("mouthOccluded") if isinstance(occ, dict) else None
+
+        accessories_list = []
+        if acc:
+            for a in acc:
+                accessories_list.append(str(a.type))
+
+        # Report
+        lines.append(f"Face number {idx}")
+        lines.append(f" - Bounding box: left={left}, top={top}, width={r.width}, height={r.height}")
+        lines.append(f" - Head Pose (Yaw): {yaw}")
+        lines.append(f" - Head Pose (Pitch): {pitch}")
+        lines.append(f" - Head Pose (Roll): {roll}")
+        lines.append(f" - Forehead occluded?: {forehead_occ}")
+        lines.append(f" - Eye occluded?: {eye_occ}")
+        lines.append(f" - Mouth occluded?: {mouth_occ}")
+        lines.append(" - Accessories:")
+        if accessories_list:
+            for a in accessories_list:
+                lines.append(f"   - {a}")
+        else:
+            lines.append("   - None")
+        lines.append("")
+
+    return "\n".join(lines).strip(), annotated
+
+
+demo = gr.Interface(
+    fn=analyze_and_annotate,
+    inputs=[
+        gr.Image(type="pil", label="Drag & drop an image"),
+        gr.Textbox(label="AI_SERVICE_KEY (paste here)", type="password", placeholder="Paste your key..."),
+    ],
+    outputs=[
+        gr.Textbox(label="Face analysis (numbers + attributes)", lines=18),
+        gr.Image(type="pil", label="Annotated image (boxes + numbers)"),
+    ],
+    title="Azure AI Face Analysis (Drag & Drop)",
+    description=f"Endpoint is hardcoded to: {AI_SERVICE_ENDPOINT}",
+)
+
+if __name__ == "__main__":
+    demo.launch()