GreenChannel14bit.py

GreenChannel14bit.py

import rawpy
import numpy as np
import matplotlib.pyplot as plt
import os


def run_14bit_audit(src_path, label, color, out_dir):

    if not os.path.exists(src_path):
        print(f"Directory not found: {src_path}")
        return

    files = [f for f in os.listdir(src_path) if f.lower().endswith('.cr2')]

    os.makedirs(out_dir, exist_ok=True)

    for filename in files:
        img_path = os.path.join(src_path, filename)

        try:
            with rawpy.imread(img_path) as raw:

                # 1. 14-bit Extraction: No post-processing, no 'smearing'
                raw_data = raw.raw_image_visible.astype(np.float32)

                # 2. Isolate Green Channel (The High-Fidelity Noise Test)
                # High-frequency Photoshop noise fails this hardware-level check.
                green_mask = np.zeros(raw_data.shape, dtype=bool)
                green_mask[0::2, 1::2] = True
                green_mask[1::2, 0::2] = True
                green_channel = raw_data[green_mask]

                # 3. Create the 14-bit Forensic Plot
                plt.figure(figsize=(10, 6))
                plt.hist(
                    green_channel,
                    bins=np.arange(0, 16385, 32),
                    color=color,
                    alpha=0.7,
                    log=True
                )

                # Hardware Reference (Anchor)
                bl = raw.black_level_per_channel[0]
                plt.axvline(
                    x=bl,
                    color='black',
                    linestyle='--',
                    label=f'Hardware Black Level ({bl})'
                )

                plt.title(f"Forensic Audit [{label}]: {filename}")
                plt.xlabel("Raw Sensor Signal (0-16383)")
                plt.ylabel("Pixel Frequency (Log Scale)")
                plt.legend()
                plt.grid(True, which="both", alpha=0.1)

                # Save with prefix to prevent overwriting across folders
                save_filename = f"{label}_{os.path.splitext(filename)[0]}.png"
                save_path = os.path.join(out_dir, save_filename)

                plt.savefig(save_path)
                plt.close()

                print(f"[✓] Saved: {save_path}")

        except Exception as e:
            print(f"[!] Error on {filename}: {e}")


# Execution targeting your specific drive paths
output_folder = "Set your target output folder here"

run_14bit_audit("Authentic CR2 Folder", "Authentic", "blue", output_folder)
run_14bit_audit("Jonas images folder", "Jonas", "red", output_folder)