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import os
# Directories
DATA_DIR = "data"
IMAGE_DIR = os.path.join(DATA_DIR, "core_images")
MODEL_DIR = "models"
OUTPUT_DIR = "output"
# Create directories if they don't exist
os.makedirs(IMAGE_DIR, exist_ok=True)
os.makedirs(MODEL_DIR, exist_ok=True)
os.makedirs(OUTPUT_DIR, exist_ok=True)
# Model parameters - adaptive to data size
NUM_CLUSTERS = 3 # Reduced default
IMAGE_SIZE = (224, 224)
BATCH_SIZE = 32
# Candidate labels for classification
CANDIDATE_LABELS = [
"gold-bearing rock",
"iron-rich rock",
"lithium-rich rock",
"copper-bearing rock",
"waste rock",
"quartz-rich rock",
"sulfide-rich rock"
]
# Public geology repositories
DATASET_SOURCES = [
{
"name": "Geoscience Australia",
"url": "https://geology.csiro.au/datasets/drill-core-images",
"description": "Australian geological survey drill core images"
},
{
"name": "USGS Mineral Resources",
"url": "https://mrdata.usgs.gov/geology/state/map-viewer.php",
"description": "US Geological Survey mineral resources data"
},
{
"name": "BGS OpenGeoscience",
"url": "https://www.bgs.ac.uk/discovering-geology/rock-library/",
"description": "British Geological Survey rock sample images"
}
]
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