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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://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() |