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import gradio as gr
from transformers import SegformerImageProcessor, AutoModelForSemanticSegmentation
from PIL import Image
import torch
import torch.nn.functional as F
import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt
processor = SegformerImageProcessor.from_pretrained("mattmdjaga/segformer_b2_clothes")
model = AutoModelForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b2_clothes")
# Renk tonlarını belirleyin (HSV'deki hue değerleri 0-180 arasında değişir)
color_map = {
"Green": 60,
"Blue": 120,
"Yellow": 30,
"Purple": 150
}
def apply_filter(image, selected_color):
image = image.convert("RGB")
inputs = processor(images=image, return_tensors="pt")
# Model çıktısını alarak segmentasyon maskesini oluşturun
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits.cpu()
# Çıktıyı orijinal görüntü boyutuna göre yeniden boyutlandırın
upsampled_logits = F.interpolate(
logits,
size=image.size[::-1],
mode="bilinear",
align_corners=False,
)
pred_seg = upsampled_logits.argmax(dim=1)[0].numpy()
hair_mask = (pred_seg == 2).astype(np.uint8)
# Orijinal görüntüyü OpenCV formatına dönüştürün ve HSV uzayına çevirin
image_cv = cv.cvtColor(np.array(image), cv.COLOR_RGB2BGR)
hsv_image = cv.cvtColor(image_cv, cv.COLOR_BGR2HSV)
# Seçilen renk için hue değeri alın
hue_value = color_map.get(selected_color, 0) # Varsayılan olarak 0 (orijinal renk tonu)
# Maske ile sadece saç bölgesini güncelleyin
hsv_image[..., 0] = np.where(hair_mask == 1, hue_value, hsv_image[..., 0])
# Saç bölgesinde doygunluk artırımı (isteğe bağlı)
hsv_image[..., 1] = np.where(hair_mask == 1, hsv_image[..., 1] * 1.5, hsv_image[..., 1])
final_image = cv.cvtColor(hsv_image, cv.COLOR_HSV2BGR)
return Image.fromarray(cv.cvtColor(final_image, cv.COLOR_BGR2RGB))
iface = gr.Interface(
fn=apply_filter,
inputs=[
gr.Image(type="pil"),
gr.Dropdown(
choices=["Green", "Blue", "Yellow", "Purple"],
label="Select Color"
)
],
outputs=gr.Image(type="numpy", label="result"),
live=False,
title="Hair Filter",
description="To change hair color, upload an image and select the color you want, then click the Submit button."
)
iface.launch(share=True)
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