Camshowrecordings/model/sam_samantha/5 -

model: name: sam_samantha version: 5 backbone: vit_h image_size: 1024 num_classes: 1 # Usually segmentation → binary mask preprocess: normalize: true mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] device: cuda

# Normalize img_norm = img_rgb.astype(np.float32) / 255.0 mean = np.array(cfg["preprocess"]["mean"]) std = np.array(cfg["preprocess"]["std"]) img_norm = (img_norm - mean) / std camshowrecordings/model/sam_samantha/5

: Performers retain a digital portfolio of their historical work. if frame_idx % stride == 0: mask =

: When it comes to AI models, especially those that might generate or interact with personal content, ethics and privacy are significant concerns. Understanding how data is used, stored, and protected is crucial. 0.406] std: [0.229

if frame_idx % stride == 0: mask = infer(frame) # binary mask (0/255) overlay = cv2.addWeighted(frame, 0.7, cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR), 0.3, 0) out.write(overlay) else: out.write(frame) # write raw frame for non‑processed indices