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from PIL import Image, ImageDraw, ImageFont
from dotenv import load_dotenv
import matplotlib.pyplot as plt
from io import BytesIO
from glob import glob
import gradio as gr
import numpy as np
import random
import requests
import base64
import boto3
import uuid
import os
import io
random.seed()
load_dotenv()
AWS_ACCESS_KEY_ID = os.environ.get('AWS_ACCESS_KEY_ID')
AWS_SECRET_ACCESS_KEY = os.environ.get('AWS_SECRET_ACCESS_KEY')
s3 = boto3.client('s3',
aws_access_key_id=AWS_ACCESS_KEY_ID,
aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
def upload2aws(img_array):
image = Image.fromarray(img_array)
buffer = io.BytesIO()
image.save(buffer, format='JPEG')
buffer.seek(0)
unique_name = str(uuid.uuid4())
s3.put_object(Bucket='predict-packages', Key=f'images_webapp_counters/{unique_name}.jpg', Body=buffer)
return None
def send2api(input_img, api_url):
buf = io.BytesIO()
plt.imsave(buf, input_img, format='jpg')
files = {'image': buf.getvalue()}
res = requests.post(api_url, files=files)
try:
res.raise_for_status()
if res.status_code != 204:
response = res.json()
except Exception as e:
print(str(e))
return response
def displaytext_yolocounter(countings, coverage):
countings_list = list(countings.items())
countings_list.sort(key = lambda x: x[1], reverse=True)
total = 0
for (y_class,c) in countings_list:
total += c
free = 100-int(coverage.split('.')[0])
text = f'free space = {free}%'+'\n\n'
for key,value in countings_list:
text += f'{key} = {value}'+'\n'
text += '\n'
text += f'total = {total}'+'\n'
return text
def testing_yolocounter(input_img):
api_url = 'http://counterid.us-east-2.elasticbeanstalk.com/predict' #'http://yolocounter-test.us-east-1.elasticbeanstalk.com/predict'
response = send2api(input_img, api_url)
countings = response['countings_scinames']
coverage = response['coverage']
detections = response['detections']
img_out = response['img_out']
img = Image.open(BytesIO(base64.b64decode(img_out)))
text = displaytext_yolocounter(countings, coverage)
return img, text
with gr.Blocks() as demo:
gr.Markdown("Submit an image with insects in a trap")
with gr.Tab("Simplified Scientific Name Count"):
with gr.Row():
input1 = gr.Image()
#output1 =[gr.Image().style(height=500, width=500), gr.Textbox(lines=20)]
output1 =[gr.Image(height=500, width=500), gr.Textbox(lines=20)]
button1 = gr.Button("Submit")
button1.click(testing_yolocounter, input1, output1)
examples_list = glob("img_examples/*.jpg")
random.shuffle(examples_list)
examples = gr.Examples(examples=examples_list[:6],inputs=[input1])
demo.launch() |