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import discord
from discord import Option, commands
import redis
import os
import random
import time
from threading import Thread
import gradio as gr
from gradio import utils
from pathlib import Path
# Function to generate auto-incremented IDs
def generate_id(key):
return r.incr(key)
def generate_progress_bar(num_labels, width=20, n=300):
print(num_labels)
percentage = int(int(num_labels) / n * 100)
completed_blocks = int(percentage * width / 100)
remaining_blocks = width - completed_blocks
progress_bar = 'β' * completed_blocks + 'β' * remaining_blocks
percentage_text = f' {num_labels}/{n} identified π¦π± '
return f'π {progress_bar} {percentage_text}'
# Redis client setup
redis_url = 'redis://default:[email protected]:7369'
r = redis.from_url(redis_url)
r.set('species_identified', 0)
# def improve_player_stats_image(ctx):
# # add 1 to the number of species identified
# value = r.get(b'species_identified').decode('utf-8')
# r.set(b'species_identified', int(value) + 1)
# xp_key = f'{ctx.author.name}:XP'.encode('utf-8')
# if not r.exists(xp_key):
# r.set(xp_key, 0)
# role_key = f'{ctx.author.name}:role'.encode('utf-8')
# if not r.exists(role_key):
# r.set(role_key, 'Naturalist')
# img_oc_key = f'{ctx.author.name}:image'.encode('utf-8')
# if not r.exists(img_oc_key):
# r.set(img_oc_key, 0)
# r.set(xp_key, int(r.get(xp_key)) + 10)
# r.set(img_oc_key, int(r.get(img_oc_key)) + 1)
bot = discord.Bot()
@bot.event
async def on_ready():
print(f"{bot.user} is ready and online!")
@bot.command(
description="Get image predictions",
options=[
Option(name="id", description="The ID of the image")
])
async def predict_image(ctx, id):
# Fetch the image data from Redis
image_data_bytes = r.hgetall(f'image:{id}'.encode('utf-8'))
image_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in image_data_bytes.items()}
path = f'https://gainforest-transparency-dashboard.s3.amazonaws.com/{image_data["awsCID"]}'
print(image_data)
message = f"**Image Observation: {id} by _{image_data['sensor']}_**"
message += "\n_Below are Top 10 predictions of AI_"
emoji_unicode_list = [chr(0x30 + i) + '\uFE0F\u20E3' for i in range(11)]
prediction_data_bytes = r.hgetall(f'prediction:{id}:1'.encode('utf-8'))
prediction_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in prediction_data_bytes.items()}
embed = discord.Embed(
title="",
description=f"Label: {prediction_data['label']}\nPredictions of our AI algorithms",
color=discord.Colour.blurple(), # Pycord provides a class with default colors you can choose from
)
embed.set_author(name=f"Image ID: {id} - AI Predictions", icon_url=ctx.author.display_avatar.url)
for i in range(1, 10):
prediction_data_bytes = r.hgetall(f'prediction:{id}:{i}'.encode('utf-8'))
prediction_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in prediction_data_bytes.items()}
species = prediction_data['label']
score = prediction_data['confidence']
# message = message + f'\n> {emoji_unicode_list[i-1]} {species} with confidence {score}'
embed.add_field(name=f'{species}', value=f'Confidence: {float(score):.4f}', inline=True)
embed.set_thumbnail(url=path)
# Send the image
await ctx.respond("Hint: You can use [Singapore Biodiversity Online](https://singapore.biodiversity.online/), [NParks Flora & Fauna Database](https://www.nparks.gov.sg/florafaunaweb), and [Singapore Birds](https://singaporebirds.com/singapore-bird-list/) to verify", embed=embed)
@bot.command(
description="Get image observation",
options=[
Option(name="id", description="The ID of the image")
])
async def image(ctx, id):
# Fetch the image data from Redis
image_data_bytes = r.hgetall(f'image:{id}'.encode('utf-8'))
image_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in image_data_bytes.items()}
print(image_data)
# Create an embed
embed = discord.Embed(color=discord.Colour.blurple())
embed.set_author(name=f"Image ID: {id}", icon_url=ctx.author.display_avatar.url)
embed.add_field(name="Sensor", value=image_data['sensor'], inline=True)
embed.add_field(name="Recorded at", value=image_data['timestamp'], inline=True)
embed.add_field(name="Recent Label", value=image_data['label'], inline=True)
embed.add_field(name="Proposed by", value=image_data['author'], inline=True)
path = f'https://gainforest-transparency-dashboard.s3.amazonaws.com/{image_data["awsCID"]}'
embed.set_image(url=path)
await ctx.respond(f"You are looking at Image ID **{id}**\n!Hint: You can use [Singapore Biodiversity Online](https://singapore.biodiversity.online/), [NParks Flora & Fauna Database](https://www.nparks.gov.sg/florafaunaweb), and [Singapore Birds](https://singaporebirds.com/singapore-bird-list/) to verify", embed=embed)
def confAutocomplete(self: discord.AutocompleteContext):
return ['low', 'medium', 'high']
def get_conf_score(confidence: str):
match confidence:
case "low":
return 0
case "medium":
return 1
case "high":
return 2
case _:
return 0
@bot.command(
description="Label image observation",
options=[
Option(name="id", description="The ID of the image"),
Option(name="label", description="The label for the image"),
Option(name="confidence", description="Choose your confidence: high, medium, low", autocomplete=confAutocomplete)
])
async def identify_image(ctx, id:int, label:str, confidence: str):
timestamp = str(time.time())
author_id = str(ctx.author_id)
role = "Hobbyist"
role_names = [role.name for role in ctx.author.roles]
if "Expert" in role_names:
role = "Expert"
label_cnt = generate_id(f'cnt:label:image:{id}')
r.hset(f'label:image:{id}:{label_cnt}'.encode('utf-8'), b'label', label.encode('utf-8'))
r.hset(f'label:image:{id}:{label_cnt}'.encode('utf-8'), b'author', ctx.author.name.encode('utf-8'))
conf_score = get_conf_score(confidence)
r.hset(f'label:image:{id}:{label_cnt}'.encode('utf-8'), b'confidence', conf_score)
r.hset(f'label:image:{id}:{label_cnt}'.encode('utf-8'), b'role', role)
r.hset(f'label:image:{id}:{label_cnt}'.encode('utf-8'), b'authorid', author_id)
r.hset(f'label:image:{id}:{label_cnt}'.encode('utf-8'), b'timestamp', timestamp)
r.hset(f'image:{id}'.encode('utf-8'), b'label', label.encode('utf-8'))
r.hset(f'image:{id}'.encode('utf-8'), b'author', ctx.author.mention.encode('utf-8'))
# Fetch the image data from Redis
image_data_bytes = r.hgetall(f'image:{id}'.encode('utf-8'))
image_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in image_data_bytes.items()}
print(image_data)
# Create an embed
embed = discord.Embed(color=discord.Colour.blurple())
embed.set_author(name=f"Image Observation {id} - New Label π", icon_url=ctx.author.display_avatar.url)
embed.add_field(name="Sensor", value=image_data['sensor'], inline=True)
embed.add_field(name="Recorded at", value=image_data['timestamp'], inline=True)
embed.add_field(name="Recent Label", value=image_data['label'], inline=True)
embed.add_field(name="Proposed by", value=image_data['author'], inline=True)
path = f'https://gainforest-transparency-dashboard.s3.amazonaws.com/{image_data["awsCID"]}'
embed.set_image(url=path)
await ctx.respond(f"{ctx.author.mention} labeled observation **{id}** as **{label}** π (Earned 10 XP)", embed=embed)
@bot.command(description="Get progress bar.")
async def progress(ctx):
value = r.get(b'species_identified').decode('utf-8')
progress_bar = generate_progress_bar(value)
await ctx.respond(progress_bar) # this decorator makes a slash command
@bot.command(description="Get sound data.") # this decorator makes a slash command
async def sound(ctx, id): # a slash command will be created with the name "ping"
# Fetch the sound data from Redis
sound_data_bytes = r.hgetall(f'sound:{id}'.encode('utf-8'))
sound_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in sound_data_bytes.items()}
# Create an embed
embed = discord.Embed(color=discord.Colour.blurple())
embed.set_author(name=f"Sound Observation {id} - Task", icon_url=ctx.author.display_avatar.url)
embed.add_field(name="Sensor", value=sound_data['sensor'], inline=True)
embed.add_field(name="Recorded at", value=sound_data['timestamp'], inline=True)
embed.add_field(name="Recent Label", value=sound_data['label'], inline=True)
embed.add_field(name="Proposed by", value=sound_data['author'], inline=True)
embed.add_field(name="Detected at Timestamp", value=sound_data['label_at'], inline=True)
await ctx.respond(f'Please listen to Sound ID **{id}** here:\nhttps://gainforest.app/observations/{sound_data["uuid"]} π¦π΅', embed=embed)
@bot.command(
description="Label sound observation",
options=[
Option(name="id", description="The ID of the sound"),
Option(name="label", description="The label for the sound"),
Option(name="timestamp", description="The timestamp of the observation"),
Option(name="confidence", description="Choose your confidence: high, medium, low", autocomplete=confAutocomplete)
])
async def identify_sound(ctx, id:int, label:str, timestamp:str, confidence: str):
timestamp = str(time.time())
author_id = str(ctx.author_id)
role = "Hobbyist"
role_names = [role.name for role in ctx.author.roles]
if "Expert" in role_names:
role = "Expert"
label_cnt = generate_id(f'cnt:label:sound:{id}')
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'label', label.encode('utf-8'))
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'author', ctx.author.name.encode('utf-8'))
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'role', role)
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'label_at', timestamp.encode('utf-8'))
conf_score = get_conf_score(confidence)
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'confidence', conf_score)
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'authorid', author_id)
r.hset(f'label:sound:{id}:{label_cnt}'.encode('utf-8'), b'timestamp', timestamp)
r.hset(f'sound:{id}'.encode('utf-8'), b'label', label.encode('utf-8'))
r.hset(f'sound:{id}'.encode('utf-8'), b'label_at', timestamp.encode('utf-8'))
r.hset(f'sound:{id}'.encode('utf-8'), b'author', ctx.author.mention.encode('utf-8'))
# Fetch the sound data from Redis
sound_data_bytes = r.hgetall(f'sound:{id}'.encode('utf-8'))
sound_data = {k.decode('utf-8'): v.decode('utf-8') for k, v in sound_data_bytes.items()}
print(sound_data)
# Create an embed
embed = discord.Embed(color=discord.Colour.blurple())
embed.set_author(name=f"Sound Observation {id} - New Label π", icon_url=ctx.author.display_avatar.url)
embed.add_field(name="Sensor", value=sound_data['sensor'], inline=True)
embed.add_field(name="Recorded at", value=sound_data['timestamp'], inline=True)
embed.add_field(name="Recent Label", value=sound_data['label'], inline=True)
embed.add_field(name="Proposed by", value=sound_data['author'], inline=True)
embed.add_field(name="Detected at Timestamp", value=sound_data['label_at'], inline=True)
await ctx.respond(f'{ctx.author.mention} labeled sound observation **{id}** as **{label}** at **{timestamp}** π (Earned 10 XP).\nListen here:\nhttps://gainforest.app/observations/{sound_data["uuid"]} π¦π΅', embed=embed)
@bot.command(
description="Get a random unlabeled image observation"
)
async def next_image(ctx):
total_images = r.get(b'cnt:image').decode('utf-8')
numbers = list(range(1, int(total_images)))
exclude_redis = r.lrange('image:accept', 0, -1)
exclude = set(int(num.decode('utf-8')) for num in exclude_redis)
numbers = [num for num in numbers if num not in exclude]
id = random.choice(numbers)
await image(ctx, id)
@bot.command(
description="Get a random unlabeled sound observation"
)
async def next_sound(ctx):
total_sound = r.get(b'cnt:sound').decode('utf-8')
numbers = list(range(1, int(total_sound)))
exclude_redis = r.lrange('image:accept', 0, -1)
exclude = set(int(num.decode('utf-8')) for num in exclude_redis)
numbers = [num for num in numbers if num not in exclude]
id = random.choice(numbers)
await sound(ctx, id)
@bot.command(
description="Check your profile"
)
async def profile(ctx):
# xp_key = f'{ctx.author.name}:XP'.encode('utf-8')
# if not r.exists(xp_key):
# r.set(xp_key, 0)
# img_oc_key = f'{ctx.author.name}:image'.encode('utf-8')
# if not r.exists(img_oc_key):
# r.set(img_oc_key, 0)
# s_oc_key = f'{ctx.author.name}:sound'.encode('utf-8')
# if not r.exists(s_oc_key):
# r.set(s_oc_key, 0)
# Create an embed
role = "Hobbyist"
role_names = [role.name for role in ctx.author.roles]
if "Expert" in role_names:
role = "Expert"
embed = discord.Embed(color=discord.Colour.blurple())
embed.set_author(name=f"{ctx.author.name} - Profile", icon_url=ctx.author.display_avatar.url)
# embed.add_field(name="**PROGRESS**", value=f"**Level**: 1\n**XP**: {r.get(xp_key).decode()}/1000\n", inline=False)
# embed.add_field(name="**STATS**", value=f"**π± Images labeled**: {r.get(img_oc_key).decode()}", inline=False)
embed.set_thumbnail(url=ctx.author.display_avatar.url)
embed.set_footer(text=f"π Role: {r.get(role).decode()}")
await ctx.respond(embed=embed)
t = Thread(target=bot.run, daemon=True, args=('MTA5NzMzMDI2MDI4NDAzNTEyMg.GNFiQP.hZC_2HLTvVAROlKKUmnVQjviT0G4wHeQq23-rs', ))
t.start()
import gradio as gr
with gr.Blocks() as demo:
gr.Markdown(Path('landing.md').read_text())
demo.launch() |