YOLOv7 / app.py
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import torch
import gradio as gr
from huggingface_hub import hf_hub_download
from PIL import Image
REPO_ID = "hiraltalsaniya/YOLOv7"
FILENAME = "best.pt"
yolov7_custom_weights = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
model = torch.hub.load('Owaiskhan9654/yolov7-1:main',model='custom', path_or_model=yolov7_custom_weights, force_reload=True) # My Github repository https://github.com/Owaiskhan9654
def object_detection(im, size=416):
results = model(im)
results.render()
return Image.fromarray(results.imgs[0])
title = "Yolov7 Custom"
image = gr.inputs.Image(shape=(416, 416), image_mode="RGB", source="upload", label="Upload Image", optional=False)
outputs = gr.outputs.Image(type="pil", label="Output Image")
Custom_description="<center>Custom Training Performed on Kaggle <a href='https://www.kaggle.com/code/owaiskhan9654/training-yolov7-on-kaggle-on-custom-dataset/notebook' style='text-decoration: underline' target='_blank'>Link</a> </center><br> <center>Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors </center> <br> <b>1st</b> class is for Person Detected<br><b>2nd</b> class is for Car Detected"
Footer = (
"<center>Model Trained by: Owais Ahmad Data Scientist at <b> Thoucentric </b> <a href=\"https://www.linkedin.com/in/owaiskhan9654/\">Visit Profile</a> <br></center>"
"<center> Model Trained Kaggle Kernel <a href=\"https://www.kaggle.com/code/owaiskhan9654/training-yolov7-on-kaggle-on-custom-dataset/notebook\">Link</a> <br></center>"
"<center> Kaggle Profile <a href=\"https://www.kaggle.com/owaiskhan9654\">Link</a> <br> </center>"
"<center> HuggingFace🤗 Model Deployed Repository <a href=\"https://huggingface.co/owaiskha9654/Yolov7_Custom_Object_Detection\">Link</a> <br></center>"
)
examples1=[["Image1.jpeg"],["Image2.jpeg"],["Image3.jpeg"],["Image4.jpeg"],["Image5.jpeg"],["Image6.jpeg"],["horses.jpeg"],["horses.jpeg"]]
Top_Title="<center>Yolov7 🚀 Custom Trained by <a href='https://www.linkedin.com/in/owaiskhan9654/' style='text-decoration: underline' target='_blank'>Owais Ahmad </center></a>🚗Car and 👦Person Detection"
css = ".output-image, .input-image {height: 50rem !important; width: 100% !important;}"
css = ".image-preview {height: auto !important;}"
gr.Interface(
fn=object_detection,
inputs=image,
outputs=outputs,
title=Top_Title,
description=Custom_description,
article=Footer,
examples=[["car-person-2.jpg"], ["car-person-2.jpg"]]).launch()