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.gitattributes

@@ -33,3 +33,19 @@ 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
+stylegan2directions/age.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/eye_distance.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/eye_eyebrow_distance.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/eye_ratio.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/eyes_open.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/gender.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/lip_ratio.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/mouth_open.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/mouth_ratio.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/nose_mouth_distance.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/nose_ratio.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/nose_tip.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/pitch.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/roll.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/smile.jpg filter=lfs diff=lfs merge=lfs -text
+stylegan2directions/yaw.jpg filter=lfs diff=lfs merge=lfs -text

app.py

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+import gradio as gr
+import numpy as np
+import torch
+import dnnlib
+import legacy
+
+# Load pretrained StyleGAN2 model
+with open("stylegan2-ffhq-config-f.pkl", "rb") as f:
+    G = legacy.load_network_pkl(f)["G_ema"].to(torch.device("cpu"))
+
+# Load gender direction vector
+gender_direction = np.load("stylegan2directions/gender.npy")
+
+def edit_gender(seed, strength):
+    rnd = np.random.RandomState(seed)
+    z = torch.from_numpy(rnd.randn(1, G.z_dim)).to(torch.float32)
+    w = G.mapping(z, None, truncation_psi=0.5)
+    w += torch.from_numpy(gender_direction).to(torch.float32) * strength
+    img = G.synthesis(w, noise_mode="const")
+    img = (img.clamp(-1, 1) + 1) * 127.5
+    img = img.permute(0, 2, 3, 1)[0].cpu().numpy().astype(np.uint8)
+    return img
+
+gr.Interface(
+    fn=edit_gender,
+    inputs=[
+        gr.Slider(0, 10000, step=1, label="Random Seed"),
+        gr.Slider(-5, 5, step=0.1, label="Gender Strength (← Feminine | Masculine →)")
+    ],
+    outputs=gr.Image(label="Generated Face"),
+    title="Gender Editing with StyleGAN2",
+    description="Move the slider to masculinize or feminize the face."
+).launch()

requirements.txt

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+gradio
+torch
+numpy
+dnnlib

stylegan2-ffhq-config-f.pkl

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stylegan2directions/age.npy

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stylegan2directions/eye_distance.npy

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stylegan2directions/eye_eyebrow_distance.npy

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stylegan2directions/gender.npy

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