add segmentation helper function

glass_segmentation_helper.py

@@ -0,0 +1,47 @@
+from PIL import Image
+import matplotlib.pyplot as plt
+import torch
+from torchvision import transforms
+from transformers import AutoModelForImageSegmentation
+
+# Load the model
+model = AutoModelForImageSegmentation.from_pretrained('briaai/RMBG-2.0', trust_remote_code=True)
+torch.set_float32_matmul_precision('high')
+model.eval()
+
+# Data settings
+image_size = (1024, 1024)
+transform_image = transforms.Compose([
+    transforms.Resize(image_size),
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+])
+
+# Get the image file path from the user
+input_image_path = input("Please enter the file path of the image: ")
+
+# Open and convert the image
+try:
+    im = Image.open(input_image_path)
+    rgb_im = im.convert('RGB')
+except FileNotFoundError:
+    print(f"Error: The file at {input_image_path} was not found.")
+    exit()
+
+# Transform the image
+input_images = transform_image(rgb_im).unsqueeze(0)
+
+# Prediction
+with torch.no_grad():
+    preds = model(input_images)[-1].sigmoid().cpu()
+
+# Process the prediction
+pred = preds[0].squeeze()
+pred_pil = transforms.ToPILImage()(pred)
+mask = pred_pil.resize(rgb_im.size)
+rgb_im.putalpha(mask)
+
+# Save the result
+output_image_path = "no_bg_image.png"
+rgb_im.save(output_image_path)
+print(f"Image with background removed saved as {output_image_path}")