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from typing import List
from PIL import Image
import pandas as pd
WHALE_CLASSES = [
"beluga",
"blue_whale",
"bottlenose_dolphin",
"brydes_whale",
"commersons_dolphin",
"common_dolphin",
"cuviers_beaked_whale",
"dusky_dolphin",
"false_killer_whale",
"fin_whale",
"frasiers_dolphin",
"gray_whale",
"humpback_whale",
"killer_whale",
"long_finned_pilot_whale",
"melon_headed_whale",
"minke_whale",
"pantropic_spotted_dolphin",
"pygmy_killer_whale",
"rough_toothed_dolphin",
"sei_whale",
"short_finned_pilot_whale",
"southern_right_whale",
"spinner_dolphin",
"spotted_dolphin",
"white_sided_dolphin",
]
WHALE_IMAGES = [
"beluga.webp",
"blue-whale.webp",
"bottlenose_dolphin.webp",
"brydes.webp",
"common_dolphin.webp",
"common_dolphin.webp",
"cuviers_beaked_whale.webp",
"common_dolphin.webp",
"false-killer-whale.webp",
"fin-whale.webp",
"fin-whale.webp",
"gray-whale.webp",
"Humpback.webp",
"killer_whale.webp",
"640x427-long-finned-pilot-whale.webp",
"melon.webp",
"minke-whale.webp",
"pantropical-spotted-dolphin.webp",
"pygmy-killer-whale.webp",
"rough-toothed-dolphin.webp",
"sei.webp",
"Whale_Short-Finned_Pilot-markedDW.png", ## Background
"640x427-southern-right-whale.jpg", ## background
"spinner.webp",
"pantropical-spotted-dolphin.webp", ## duplicate also used for
"640x427-atlantic-white-sided-dolphin.jpg", ##background
]
WHALE_REFERENCES = [
"https://www.fisheries.noaa.gov/species/beluga-whale",
"https://www.fisheries.noaa.gov/species/blue-whale",
"https://www.fisheries.noaa.gov/species/common-bottlenose-dolphin",
"https://www.fisheries.noaa.gov/species/brydes-whale",
"https://en.wikipedia.org/wiki/Commerson's_dolphin",
#"commersons_dolphin - reference missing - classification to be verified", ## class matching to be verified
"https://www.fisheries.noaa.gov/species/short-beaked-common-dolphin",
"https://www.fisheries.noaa.gov/species/cuviers-beaked-whale",
"https://en.wikipedia.org/wiki/Dusky_dolphin",
#"dusky_dolphin - reference missing - classification to be verified", ## class matching to be verified
"https://www.fisheries.noaa.gov/species/false-killer-whale",
"https://www.fisheries.noaa.gov/species/fin-whale",
"https://www.fisheries.noaa.gov/species/frasers-dolphin",
#"frasiers_dolphin - reference missing - classification to be verified", ## class matching to be verified
"https://www.fisheries.noaa.gov/species/gray-whale",
"https://www.fisheries.noaa.gov/species/humpback-whale",
"https://www.fisheries.noaa.gov/species/killer-whale",
"https://www.fisheries.noaa.gov/species/long-finned-pilot-whale",
"https://www.fisheries.noaa.gov/species/melon-headed-whale",
"https://www.fisheries.noaa.gov/species/minke-whale",
"https://www.fisheries.noaa.gov/species/pantropical-spotted-dolphin",
"https://www.fisheries.noaa.gov/species/pygmy-killer-whale",
"https://www.fisheries.noaa.gov/species/rough-toothed-dolphin",
"https://www.fisheries.noaa.gov/species/sei-whale",
"https://www.fisheries.noaa.gov/species/short-finned-pilot-whale",
"https://www.fisheries.noaa.gov/species/southern-right-whale",
"https://www.fisheries.noaa.gov/species/spinner-dolphin",
"https://www.fisheries.noaa.gov/species/pantropical-spotted-dolphin",
"https://www.fisheries.noaa.gov/species/atlantic-white-sided-dolphin",
]
# Create a dataframe
df_whale_img_ref = pd.DataFrame(
{
"WHALE_CLASSES": WHALE_CLASSES,
"WHALE_IMAGES": WHALE_IMAGES,
"WHALE_REFERENCES": WHALE_REFERENCES,
}
).set_index("WHALE_CLASSES")
def format_whale_name(whale_class:str) -> str:
"""
Formats a whale class name for display
Args:
whale_class (str): The class name of the whale, with words separated by underscores.
Returns:
str: The formatted whale name with spaces instead of underscores and each word capitalized.
"""
whale_name = whale_class.replace("_", " ").title()
return whale_name
def display_whale(whale_classes:List[str], i:int, viewcontainer=None):
"""
Display whale image and reference to the provided viewcontainer.
Args:
whale_classes (List[str]): A list of whale class names.
i (int): The index of the whale class to display.
viewcontainer: The container to display the whale information. If
not provided, use the current streamlit context (works via
'with `container`' syntax)
Returns:
None
TODO: how to find the object type of viewcontainer.? they are just "deltagenerators" but
we want the result of the generator.. In any case, it works ok with either call signature.
"""
import streamlit as st
if viewcontainer is None:
viewcontainer = st
# validate the input i should be within the range of the whale_classes
if i >= len(whale_classes):
raise ValueError(f"Index {i} is out of range. The whale_classes list has only {len(whale_classes)} elements.")
# validate the existence of the whale class in the dataframe as a row key
if whale_classes[i] not in df_whale_img_ref.index:
raise ValueError(f"Whale class {whale_classes[i]} not found in the dataframe.")
viewcontainer.markdown(
"### :whale: #" + str(i + 1) + ": " + format_whale_name(whale_classes[i])
)
image = Image.open("images/references/" + df_whale_img_ref.loc[whale_classes[i], "WHALE_IMAGES"])
viewcontainer.image(image, caption=df_whale_img_ref.loc[whale_classes[i], "WHALE_REFERENCES"])
# link st.markdown(f"[{df.loc[whale_classes[i], 'WHALE_REFERENCES']}]({df.loc[whale_classes[i], 'WHALE_REFERENCES']})") |