Upload usage_demo_bioscan5m.py

usage_demo_bioscan5m.py

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+"""
+BIOSCAN-5M Dataset Loader
+
+Author: Zahra Gharaee (https://github.com/zahrag)
+License: MIT License
+Description:
+    This script serves as a usage demo for loading and accessing the BIOSCAN-5M dataset,
+    which includes millions of annotated insect images along with associated metadata for machine learning and biodiversity research.
+    It demonstrates how to use the dataset loader to access multiple image resolutions (e.g., cropped and original)
+    and predefined splits (e.g., training, validation, pretraining).
+    The demo integrates with the Hugging Face `datasets` library, showcasing how to load
+    the dataset locally or from the Hugging Face Hub for seamless data preparation and machine learning workflows.
+"""
+
+import matplotlib.pyplot as plt
+from datasets import load_dataset
+
+
+def plot_image_with_metadata(ex):
+
+    image = ex["image"]
+
+    # Define the metadata fields to show
+    fields_to_show = [
+        "processid", "sampleid", "phylum", "class", "order", "family", "subfamily", "genus", "species",
+        "dna_bin", "dna_barcode", "country", "province_state", "coord-lat", "coord-lon",
+        "image_measurement_value", "area_fraction", "scale_factor", "split"
+    ]
+
+    # Prepare metadata as formatted strings
+    metadata_lines = []
+    for cnt, field in enumerate(fields_to_show):
+        value = ex.get(field, "N/A")
+        if field == "dna_barcode" and value not in ("N/A", None, ""):
+            value = value[:10] + " ... " + f"({len(value)} bp)"  # bp: base pairs
+        if field == "image_measurement_value" and value not in (None, "", "N/A"):
+            value = int(value)
+        metadata_lines.append(f"{cnt + 1}- {field}: {value}")
+
+    fig, axs = plt.subplots(1, 2, figsize=(12, 6), gridspec_kw={'width_ratios': [1.2, 2]})
+    plt.subplots_adjust(wspace=0.1)
+    fig.suptitle(f"Image and Metadata: {ex.get('processid', '')}", fontsize=14)
+
+    # Left: metadata
+    axs[0].axis("off")
+    metadata_text = "\n".join(metadata_lines)
+    axs[0].text(0, 0.9, metadata_text, fontsize=14, va='top', ha='left', transform=axs[0].transAxes, wrap=True)
+
+    # Right: image
+    axs[1].imshow(image)
+    axs[1].axis("off")
+
+    plt.tight_layout()
+    plt.show()
+
+
+def main():
+
+    ds_val = load_dataset("bioscan5m.py", name="cropped_256_eval", split="validation", trust_remote_code=True)
+    print(f"{ds_val.description}{ds_val.license}{ds_val.citation}")
+
+    # Print and visualize a few examples
+    samples_to_show = 10
+    cnt = 1
+    for i, sp in enumerate(ds_val):
+        plot_image_with_metadata(sp)
+        if cnt == samples_to_show:
+            break
+        cnt += 1
+
+if __name__ == '__main__':
+    main()
+
+
+