Initial commit

lab6-steganography/modes/__init__.py

@@ -0,0 +1,6 @@
+__all__ = ["EmbedMode", "ExtractMode", "AnalyzeQuality", "GenerateMode"]
+
+from .embed_mode import EmbedMode
+from .extract_mode import ExtractMode
+from .analyze_quality import AnalyzeQuality
+from .generate_mode import GenerateMode

lab6-steganography/modes/analyze_quality.py

@@ -0,0 +1,41 @@
+from __future__ import annotations
+from dataclasses import dataclass
+from typing import Dict, List
+import numpy as np
+
+from entities.rgb_image512 import RgbImage512
+from entities.color_space import ColorSpace
+from entities.psnr_metric import PsnrMetric
+
+
+@dataclass
+class AnalyzeQuality:
+    """CLI-режим расчёта метрик качества."""
+
+    def run(
+        self,
+        original_path: str,
+        stego_path: str,
+        space: str = "ycbcr",
+        metrics: List[str] = None,
+    ) -> Dict[str, float]:
+        """Посчитать метрики между изображениями."""
+        if metrics is None:
+            metrics = ["psnr"]
+        metrics = [m.lower() for m in metrics]
+        if any(m != "psnr" for m in metrics):
+            raise ValueError("Поддерживается только метрика PSNR.")
+
+        orig = RgbImage512.from_file(original_path).to_array()
+        steg = RgbImage512.from_file(stego_path).to_array()
+
+        if space.lower() == "ycbcr":
+            a = ColorSpace.rgb_to_ycbcr(orig)
+            b = ColorSpace.rgb_to_ycbcr(steg)
+        elif space.lower() == "rgb":
+            a, b = orig, steg
+        else:
+            raise ValueError("space должен быть 'rgb' или 'ycbcr'.")
+
+        psnr = PsnrMetric().psnr(a, b)
+        return {"psnr": float(psnr)}

lab6-steganography/modes/embed_mode.py

@@ -0,0 +1,40 @@
+
+from __future__ import annotations
+from dataclasses import dataclass
+from typing import Dict
+
+from entities.rgb_image512 import RgbImage512
+from entities.label64 import Label64
+from entities.sequence8 import Sequence8
+from steg.embedder import Embedder
+from steg.extractor import Extractor
+from steg.component_pipeline import ComponentPipeline
+
+
+@dataclass
+class EmbedMode:
+    """CLI-режим встраивания метки в изображение."""
+
+    def run(
+        self,
+        input_path: str,
+        label_path: str,
+        output_path: str,
+        channel: str,
+        seq0: str,
+    ) -> Dict[str, str]:
+        """Выполнить встраивание и сохранить результат."""
+        rgb = RgbImage512.from_file(input_path)
+        label = Label64.from_image(label_path)
+        seq = Sequence8.from_string(seq0)
+
+        pipeline = ComponentPipeline(channel=channel, embedder=Embedder(), extractor=Extractor())
+        rgb_out = pipeline.embed_rgb(rgb, label, seq)
+        rgb_out.save(output_path)
+
+        return {
+            "status": "ok",
+            "output": output_path,
+            "channel": channel,
+            "seq0": seq0,
+        }

lab6-steganography/modes/extract_mode.py

@@ -0,0 +1,38 @@
+
+from __future__ import annotations
+from dataclasses import dataclass
+from typing import Dict
+
+from entities.rgb_image512 import RgbImage512
+from entities.label64 import Label64
+from entities.sequence8 import Sequence8
+from steg.embedder import Embedder
+from steg.extractor import Extractor
+from steg.component_pipeline import ComponentPipeline
+
+
+@dataclass
+class ExtractMode:
+    """CLI-режим извлечения метки из изображения."""
+
+    def run(
+        self,
+        input_path: str,
+        output_path: str,
+        channel: str,
+        seq0: str,
+    ) -> Dict[str, str]:
+        """Извлечь метку и сохранить 64x64 PNG."""
+        rgb = RgbImage512.from_file(input_path)
+        seq = Sequence8.from_string(seq0)
+
+        pipeline = ComponentPipeline(channel=channel, embedder=Embedder(), extractor=Extractor())
+        label: Label64 = pipeline.extract_from_rgb(rgb, seq)
+        label.to_image(output_path)
+
+        return {
+            "status": "ok",
+            "output": output_path,
+            "channel": channel,
+            "seq0": seq0,
+        }

lab6-steganography/modes/generate_mode.py

@@ -0,0 +1,40 @@
+
+from __future__ import annotations
+from dataclasses import dataclass
+from typing import Dict, Optional
+import numpy as np
+from PIL import Image
+
+from generators.gradient_generator import GradientGenerator
+from generators.chessboard_generator import ChessboardGenerator
+
+
+@dataclass
+class GenerateMode:
+    """CLI-режим генерации изображений: gradient/chess."""
+
+    def run(
+        self,
+        kind: str,
+        size: int,
+        channels: int,
+        output_path: str,
+        tile: Optional[int] = None,
+    ) -> Dict[str, str]:
+        """Сгенерировать изображение и сохранить в файл."""
+        if kind == "gradient":
+            arr = GradientGenerator.make(size=size, channels=channels)
+        elif kind == "chess":
+            t = 32 if tile is None else int(tile)
+            arr = ChessboardGenerator.make(size=size, channels=channels, tile=t)
+        else:
+            raise ValueError("kind должен быть 'gradient' или 'chess'.")
+
+        mode = "L" if channels == 1 else "RGB"
+        if arr.ndim == 2:
+            img = Image.fromarray(arr, mode=mode)
+        else:
+            img = Image.fromarray(arr.astype(np.uint8), mode=mode)
+        img.save(output_path)
+
+        return {"status": "ok", "kind": kind, "size": str(size), "channels": str(channels), "output": output_path}