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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() |