app.py

import gradio as gr
import cv2
from geti_sdk.deployment import Deployment
from geti_sdk.utils import show_image_with_annotation_scene
import numpy as np
from urllib.request import urlopen

# Step 1: Load the deployment
deployment = Deployment.from_folder("deployment")
deployment.load_inference_models(device="CPU")


def resize_image(image, target_dimension):
    height, width = image.shape[:2]
    max_dimension = max(height, width)
    scale_factor = target_dimension / max_dimension
    new_width = int(width * scale_factor)
    new_height = int(height * scale_factor)
    resized_image = cv2.resize(image, (new_width, new_height))
    return resized_image


def infer(image=None, url:str=None):
    if image is None and url is None:
        return [None,'no image or URL provided']

    if image is None:
        if isinstance(url, str):
            req = urlopen(url)
            arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
            image = cv2.imdecode(arr, -1)
            if image is None:
                return [None, f'Unable to fetch image from {url}']
            image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

    image = resize_image(image, 1200)
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    prediction = deployment.infer(image)
    output = show_image_with_annotation_scene(cv2.cvtColor(image, cv2.COLOR_BGR2RGB), prediction, show_results=False)
    output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
    return [output, prediction.overview]


interface = gr.Interface(fn=infer, 
             inputs=['image', 'text'],
             outputs=['image', 'text'],
             allow_flagging='manual',
             flagging_dir='flagged',
             examples=[["no_bird.jpg", ""],
                       ["bird_example.jpg",""],
                       [None,"https://upload.wikimedia.org/wikipedia/commons/9/9a/Pinz%C3%B3n_azul_de_Gran_Canaria_%28macho%29%2C_M._A._Pe%C3%B1a.jpg"]
                       [None, "https://upload.wikimedia.org/wikipedia/commons/2/2f/Phaethon_lepturus_%28Warwick%2C_Bermuda%29_%28cropped%29.jpg"]
                       ])

interface.launch()