demo

app.py

@@ -1,7 +1,72 @@
 import gradio as gr
+import tensorflow as tf
+import tensorflow_hub as hub
+import cv2
+import numpy as np
+import tempfile
+import json
+import uuid
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load face detector
+detector = hub.load("https://tfhub.dev/tensorflow/ssd_mobilenet_v2/fpnlite_320x320/1")
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def detect_faces(image):
+    """Runs TensorFlow SSD model to detect faces in an image."""
+    input_tensor = tf.convert_to_tensor([image], dtype=tf.uint8)
+    detector_output = detector(input_tensor)
+    boxes = detector_output['detection_boxes'][0].numpy()
+    scores = detector_output['detection_scores'][0].numpy()
+    return boxes[scores > 0.5]
+
+def euclidean_hash(box):
+    """Simple hash based on box centroid"""
+    y1, x1, y2, x2 = box
+    cx = (x1 + x2) / 2
+    cy = (y1 + y2) / 2
+    return str(uuid.uuid5(uuid.NAMESPACE_DNS, f"{cx:.4f}-{cy:.4f}"))
+
+def process_frame(frame):
+    h, w, _ = frame.shape
+    boxes = detect_faces(frame)
+    result = []
+    for box in boxes:
+        y1, x1, y2, x2 = box
+        x1a, y1a, x2a, y2a = int(x1 * w), int(y1 * h), int(x2 * w), int(y2 * h)
+        face_id = euclidean_hash(box)
+        result.append({
+            "id": face_id,
+            "coords": [x1a, y1a, x2a, y2a]
+        })
+        cv2.rectangle(frame, (x1a, y1a), (x2a, y2a), (0, 255, 0), 2)
+        cv2.putText(frame, face_id[:6], (x1a, y1a - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+    return frame, json.dumps(result, indent=2)
+
+def video_handler(video):
+    cap = cv2.VideoCapture(video)
+    frames = []
+    last_json = {}
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        tagged_frame, json_result = process_frame(frame)
+        frames.append(tagged_frame)
+        last_json = json_result
+    cap.release()
+    out_path = tempfile.mktemp(suffix=".mp4")
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter(out_path, fourcc, 15, (frames[0].shape[1], frames[0].shape[0]))
+    for f in frames:
+        out.write(f)
+    out.release()
+    return out_path, last_json
+
+iface = gr.Interface(
+    fn=video_handler,
+    inputs=gr.Video(),
+    outputs=[gr.Video(label="Tagged Video"), gr.Textbox(label="Detected Faces JSON")],
+    title="Multi-Face Recognizer with Unique ID Hashes",
+    description="Upload or stream a video. Each detected face will be tagged with a short unique hash."
+)
+
+iface.launch()

requirements.txt

@@ -0,0 +1,5 @@
+gradio==4.29.0
+opencv-python-headless==4.9.0.80
+tensorflow==2.16.1
+tensorflow-hub==0.16.1
+numpy==1.26.4