Add JPEG and Simple WebP compression algorithms

Author: sszacillo

src/compression/jpeg_compression_algorithm.py

@@ -0,0 +1,71 @@
+from algorithm import Algorithm
+import numpy as np
+import cv2
+import matplotlib.pyplot as plt
+
+class JPEGCompression(Algorithm):
+    Q_BASE = np.array([
+        [16, 11, 10, 16, 24, 40, 51, 61],
+        [12, 12, 14, 19, 26, 58, 60, 55],
+        [14, 13, 16, 24, 40, 57, 69, 56],
+        [14, 17, 22, 29, 51, 87, 80, 62],
+        [18, 22, 37, 56, 68, 109, 103, 77],
+        [24, 35, 55, 64, 81, 104, 113, 92],
+        [49, 64, 78, 87, 103, 121, 120, 101],
+        [72, 92, 95, 98, 112, 100, 103, 99]
+    ], dtype=np.float32)
+
+    @staticmethod
+    def get_params() -> dict:
+        return {"quality": 85, "compression_level": 1.0}
+
+    @staticmethod
+    def process_block(block, quantization_table):
+        block = block.astype(np.float32) - 128  # Konwersja na float32 przed DCT
+        dct_block = cv2.dct(block)
+        quantized = np.round(dct_block / quantization_table)
+        dequantized = quantized * quantization_table
+        reconstructed = cv2.idct(dequantized) + 128
+        return np.clip(reconstructed, 0, 255).astype(np.uint8)  # Konwersja z powrotem do uint8
+
+
+    @staticmethod
+    def compress(image: np.ndarray, params: dict) -> np.ndarray:
+        compression_level = params.get("compression_level", 1.0)
+        
+        if len(image.shape) == 2:  
+            image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
+        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+        Q_Y = np.clip(JPEGCompression.Q_BASE * compression_level, 1, 255)
+        Q_C = np.clip(JPEGCompression.Q_BASE * 1.2 * compression_level, 1, 255)
+        
+        image_ycrcb = cv2.cvtColor(image, cv2.COLOR_BGR2YCrCb)
+        h, w, _ = image_ycrcb.shape
+        compressed_image = np.zeros_like(image_ycrcb, dtype=np.uint8)
+        
+        for channel in range(3):
+            channel_data = image_ycrcb[:, :, channel]
+            
+            h_pad = (8 - (h % 8)) % 8
+            w_pad = (8 - (w % 8)) % 8
+            channel_padded = np.pad(channel_data, ((0, h_pad), (0, w_pad)), mode='constant', constant_values=128)
+            
+            h_new, w_new = channel_padded.shape
+            compressed_channel = np.zeros((h_new, w_new), dtype=np.float32)
+            
+            Q = Q_Y if channel == 0 else Q_C
+
+            for i in range(0, h_new, 8):
+                for j in range(0, w_new, 8):
+                    block = channel_padded[i:i+8, j:j+8]
+                    processed_block = JPEGCompression.process_block(block, Q)
+                    compressed_channel[i:i+8, j:j+8] = processed_block
+            
+            compressed_image[:h, :w, channel] = np.clip(compressed_channel[:h, :w], 0, 255).astype(np.uint8)
+        
+        compressed_rgb = cv2.cvtColor(compressed_image, cv2.COLOR_YCrCb2RGB)
+        return compressed_rgb
+
+    @staticmethod
+    def decompress(image: np.ndarray, params: dict) -> np.ndarray:
+        return image

src/compression/webp_compression.py

@@ -0,0 +1,26 @@
+from algorithm import Algorithm
+import numpy as np
+import zlib
+
+class SimpleWebPCompression(Algorithm):
+    """
+    Simple WebP-like compression algorithm.
+    """
+
+    @staticmethod
+    def get_params() -> dict:
+        return {"quality": "16"}
+
+    @staticmethod
+    def compress(data: np.ndarray, params: dict[str, str]) -> np.ndarray:
+        quality = int(params.get("quality", 16))
+        quantized_array = (data // (256 // quality)) * (256 // quality)
+        compressed_data = zlib.compress(quantized_array.tobytes(), level=9)
+        return np.frombuffer(compressed_data, dtype=np.uint8)
+
+    @staticmethod
+    def decompress(data: np.ndarray, params: dict[str, str], image_size: tuple) -> np.ndarray:
+        quality = int(params.get("quality", 16))
+        decompressed_data = zlib.decompress(data)
+        img_array = np.frombuffer(decompressed_data, dtype=np.uint8).reshape(image_size)
+        return (img_array // (256 // quality)) * (256 // quality)