jeffrey1963/Cattle-Elk-R5

1from PIL import Image2 3def load_and_crop_image(path="Carson_map.png", crop_box=(15, 15, 1000, 950)):4    img = Image.open(path).convert("RGB")5    cropped_img = img.crop(crop_box)6    return cropped_img7 8 9from sklearn.cluster import KMeans10import numpy as np11 12def cluster_image(cropped_img, n_clusters=6):13    img_array = np.array(cropped_img)14    pixels = img_array.reshape(-1, 3)15    kmeans = KMeans(n_clusters=n_clusters, random_state=42).fit(pixels)16    labels = kmeans.labels_.reshape(img_array.shape[:2])17    return labels18 19 20from collections import Counter21import numpy as np22 23def build_parcel_map(clustered_img, grid_size=20):24    height, width = clustered_img.shape25    n_rows = height // grid_size26    n_cols = width // grid_size27    parcel_map = np.zeros((n_rows, n_cols), dtype=int)28 29    for i in range(n_rows):30        for j in range(n_cols):31            patch = clustered_img[i*grid_size:(i+1)*grid_size, j*grid_size:(j+1)*grid_size].flatten()32            dominant = Counter(patch).most_common(1)[0][0]33            parcel_map[i, j] = dominant34 35    return parcel_map, n_rows, n_cols36 37 38import matplotlib.pyplot as plt39import matplotlib.patches as mpatches40from matplotlib.colors import ListedColormap41 42def plot_parcel_map(parcel_map, cluster_labels, land_colors, title="25×25 Land Parcels by Land Type"):43    cmap = ListedColormap(land_colors)44    plt.figure(figsize=(10, 8))45    plt.imshow(parcel_map, cmap=cmap, origin='upper')46    legend_patches = [mpatches.Patch(color=land_colors[i], label=cluster_labels[i]) for i in cluster_labels]47    plt.legend(handles=legend_patches, bbox_to_anchor=(1.05, 1), loc='upper left', title="Land Type")48    plt.title(title)49    plt.axis('off')50    plt.tight_layout()51    plt.show()52 53def plot_parcel_map_to_file(parcel_map, cluster_labels, land_colors, save_path="clustered_map.png", title="25×25 Land Parcels by Land Type"):54    cmap = ListedColormap(land_colors)55    fig, ax = plt.subplots(figsize=(10, 8))56    cax = ax.imshow(parcel_map, cmap=cmap, origin='upper')57    legend_patches = [mpatches.Patch(color=land_colors[i], label=cluster_labels[i]) for i in cluster_labels]58    ax.legend(handles=legend_patches, bbox_to_anchor=(1.05, 1), loc='upper left', title="Land Type")59    ax.set_title(title)60    ax.axis('off')61    plt.tight_layout()62    plt.savefig(save_path)63    plt.close(fig)64 65 66def get_cluster_labels():67    return {68        0: 'Pasture/Desert',69        1: 'Productive Grass',70        2: 'Pasture/Desert',71        3: 'Riparian Sensitive Zone',72        4: 'Rocky Area',73        5: 'Water'74    }75 76 77def get_land_colors():78    return ['#dfb867', '#a0ca76', '#dfb867', '#5b8558', '#888888', '#3a75a8']79 80 81 82 83 84