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Parent(s):
829db09
Create app.py
Browse files
app.py
ADDED
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import gradio as gr
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import cv2
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import requests
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import os
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from ultralytics import YOLO
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file_urls = ["https://www.dropbox.com/scl/fi/i582tgw95r0f8i8cssmx0/images.jpg?rlkey=fa3d74yaj0bh941jo67n0elns&dl=0"
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# 'https://www.dropbox.com/scl/fi/z4tnnills03s1o4evbqpl/download.jpg?rlkey=gmh63kexnnjcva6ahzo2wfmsd&dl=0'
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]
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def download_file(url, save_name):
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url = url
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if not os.path.exists(save_name):
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file = requests.get(url)
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open(save_name, 'wb').write(file.content)
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for i, url in enumerate(file_urls):
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if 'mp4' in file_urls[i]:
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download_file(
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file_urls[i],
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f"video.mp4"
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)
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else:
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download_file(
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file_urls[i],
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f"image_{i}.jpg"
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)
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model = YOLO('best.pt')
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path = [['images.jpg'],['images_1.png'],['image/i1.png'],['image/i2.png'],['image/i3.png']]
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# ,['image/i4.png'],['image/i5.png'],['image/i6.png'],['image/i7.png'],['image/i8.png'],['image/i9.png'],['image/i10.png'],['image/i11.png'],
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# ['image/i12.png'],['image/i13.png'],['image/i14.png'],['image/i15.png'],['image/i16.png'],['image/i17.png'],['image/i18.png'],['image/i19.png'],
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# ['image/i20.png'],['image/i21.png'],['image/i22.png'],['image/i23.png'],['image/i24.png'],['image/i25.png'],['image/i26.png'],['image/i27.png'],['image/i28.png']]
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# video_path = [['video.mp4']]
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def show_preds_image(image_path):
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image = cv2.imread(image_path)
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outputs = model.predict(source=image_path)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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cv2.rectangle(
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image,
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(int(det[0]), int(det[1])),
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(int(det[2]), int(det[3])),
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color=(0, 0, 255),
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thickness=2,
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lineType=cv2.LINE_AA
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)
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return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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inputs_image = [
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gr.components.Image(type="filepath", label="Input Image"),
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]
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outputs_image = [
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gr.components.Image(type="numpy", label="Output Image"),
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]
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interface_image = gr.Interface(
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fn=show_preds_image,
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inputs=inputs_image,
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outputs=outputs_image,
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title="Airport Luggage Weapon Detector app",
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examples=path,
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cache_examples=False,
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)
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def show_preds_video(video_path):
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cap = cv2.VideoCapture(video_path)
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while(cap.isOpened()):
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ret, frame = cap.read()
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if ret:
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frame_copy = frame.copy()
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outputs = model.predict(source=frame)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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cv2.rectangle(
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frame_copy,
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(int(det[0]), int(det[1])),
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(int(det[2]), int(det[3])),
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color=(0, 0, 255),
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thickness=2,
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lineType=cv2.LINE_AA
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)
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yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
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inputs_video = [
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gr.components.Video(),
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]
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outputs_video = [
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gr.components.Image(),
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]
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interface_video = gr.Interface(
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fn=show_preds_video,
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inputs=inputs_video,
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outputs=outputs_video,
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title="Airport Luggage Weapon Detector",
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cache_examples=False,
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)
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MORE = """ ## TRY Other Models
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![imagea](image_path 'image/i5.png')
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### Instant Image: 4k images in 5 Second -> https://huggingface.co/spaces/KingNish/Instant-Image
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"""
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gr.Markdown(MORE)
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gr.TabbedInterface(
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[interface_image, interface_video],
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tab_names=['Image inference', 'Video inference']
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).queue().launch()
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