Initial commit

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.gitignore

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+/notebooks/yolo11n-cls.pt
+/notebooks/Age_Detection/v1_epochs_10_imgsz_64/weights
+/notebooks/Gender_Detection/v1_epochs_10_imgsz_64/weights
+IMG_20250823_130158.jpg
+/dataset

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/.name

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+Age_Gender_Predictor

.idea/Age_Gender_Predictor.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.10 (Age_Predictor)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
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+  </component>
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+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Age_Gender_Predictor.iml" filepath="$PROJECT_DIR$/.idea/Age_Gender_Predictor.iml" />
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+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/Age-Gender-Detector" vcs="Git" />
+  </component>
+</project>

README.md

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+---
+title: Age Gender Detector
+emoji: 🐠
+colorFrom: blue
+colorTo: yellow
+sdk: gradio
+sdk_version: 5.44.1
+app_file: app.py
+pinned: false
+short_description: Detecting Face and Personality using YOLO
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import cv2
+
+from huggingface_hub import hf_hub_download
+from ultralytics import YOLO
+from supervision import Detections
+
+
+def detect_age_or_gender(face, model):
+    result = model(face, verbose=False)
+    index_mapping = result[0].names
+
+    result_index = result[0].probs.top1
+    label = index_mapping[result_index]
+
+    return label
+
+
+def crop_face(img, bbox):
+    return img[bbox[1]:bbox[3], bbox[0]:bbox[2]]
+
+
+def detect_age_gender(image):
+    new_image = image.copy()
+    fd_output = fd_model(image, verbose=False)
+
+    results = Detections.from_ultralytics(fd_output[0])
+
+    for ind, result in enumerate(results):
+        if len(results.xyxy[ind]) > 0:
+            bbox = [int(b) for b in results.xyxy[ind]]  # xyxy = [x1, y1, x2, y2]
+            confidence = results.confidence[ind]
+            face = crop_face(image, bbox)
+            gender = detect_age_or_gender(face, gd_model)
+            age = detect_age_or_gender(face, ad_model)
+            new_image = cv2.rectangle(new_image, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (36, 255, 12), 3)
+            cv2.putText(new_image,
+                        f"{gender}, {age} ({confidence:.2f})",
+                        (bbox[0], bbox[1] - 10),
+                        cv2.FONT_HERSHEY_SIMPLEX,
+                        1.0, (36, 255, 12), 2)
+
+    return new_image
+
+
+def init_models():
+    # ----------------------- CONFIGURATIONS ----------------------- #
+
+    FACE_DETECTION_MODEL = "arnabdhar/YOLOv8-Face-Detection"
+    GENDER_DETECTION_MODEL = r".\models\gender.pt"
+    AGE_DETECTION_MODEL = r".\models\age.pt"
+
+    # -------------------------------------------------------------- #
+    # Load Face Detection (fd) Model
+    model_path = hf_hub_download(repo_id=FACE_DETECTION_MODEL, filename="model.pt")
+    fd_model = YOLO(model_path)
+
+    # Load Gender Detection (gd) Model
+    gd_model = YOLO(GENDER_DETECTION_MODEL)
+
+    # Load Age Detection (ad) Model
+    ad_model = YOLO(AGE_DETECTION_MODEL)
+
+    return fd_model, gd_model, ad_model
+
+
+fd_model, gd_model, ad_model = init_models()
+
+
+# Gradio Interface
+with gr.Blocks(theme=gr.themes.Glass()) as demo:
+    gr.Markdown("# Age and Gender Detection App")
+    gr.Markdown("Click a button to either upload an image or use your camera for real-time detection.")
+
+    with gr.Tab("Single Image"):
+        gr.Interface(fn=detect_age_gender,
+                     inputs=gr.Image(type="numpy", label="Input Image", width="100%", height=640),
+                     outputs=gr.Image(type="numpy", label="Output Image", width="100%", height=640))
+
+    with gr.Tab("Video Capture"):
+        # The webcam image component. The `sources=["webcam"]` and `streaming=True`
+        # are the key components for real-time video processing.
+        webcam_input = gr.Image(
+            sources=["webcam"],
+            streaming=True,
+            interactive=True,
+            type="numpy",
+            label="Webcam Input",
+            width="100%",
+            height=480
+        )
+
+        # The output component where the processed video will be displayed.
+        output_image = gr.Image(
+            label="Processed Feed",
+            width="100%",
+            height=480
+        )
+
+        # The `stream()` method automatically calls the `process_frame` function
+        # for each frame of the video feed.
+        webcam_input.stream(detect_age_gender,
+                            inputs=webcam_input,
+                            outputs=output_image)
+
+demo.launch()

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models/gender.pt

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notebooks/Age_Detection/v1_epochs_10_imgsz_64/args.yaml

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+task: classify
+mode: train
+model: yolo11n-cls.pt
+data: D:\Documents\Personal Projects\Age_Predictor\dataset\age
+epochs: 50
+time: null
+patience: 100
+batch: 16
+imgsz: 64
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+device: '0'
+workers: 8
+project: Age_Detection
+name: v1_epochs_10_imgsz_64
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+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: Age_Detection\v1_epochs_10_imgsz_64

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notebooks/Gender_Detection/v1_epochs_10_imgsz_64/args.yaml

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+mode: train
+model: yolo11n-cls.pt
+data: D:\Documents\Personal Projects\Age_Predictor\dataset
+epochs: 10
+time: null
+patience: 100
+batch: 16
+imgsz: 64
+save: true
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+name: v1_epochs_10_imgsz_64
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