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| import gradio as gr | |
| #import torch | |
| import yolov7 | |
| # | |
| # from huggingface_hub import hf_hub_download | |
| from huggingface_hub import HfApi | |
| # Images | |
| #torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg', 'zidane.jpg') | |
| #torch.hub.download_url_to_file('https://raw.githubusercontent.com/obss/sahi/main/tests/data/small-vehicles1.jpeg', 'small-vehicles1.jpeg') | |
| def yolov7_inference( | |
| image: gr.inputs.Image = None, | |
| model_path: gr.inputs.Dropdown = None, | |
| image_size: gr.inputs.Slider = 640, | |
| conf_threshold: gr.inputs.Slider = 0.25, | |
| iou_threshold: gr.inputs.Slider = 0.45, | |
| ): | |
| """ | |
| YOLOv7 inference function | |
| Args: | |
| image: Input image | |
| model_path: Path to the model | |
| image_size: Image size | |
| conf_threshold: Confidence threshold | |
| iou_threshold: IOU threshold | |
| Returns: | |
| Rendered image | |
| """ | |
| model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False) | |
| model.conf = conf_threshold | |
| model.iou = iou_threshold | |
| results = model([image], size=image_size) | |
| return results.render()[0] | |
| inputs = [ | |
| gr.inputs.Image(type="pil", label="Input Image"), | |
| gr.inputs.Dropdown( | |
| choices=[ | |
| "alshimaa/model_baseline", | |
| "alshimaa/model_yolo7", | |
| #"kadirnar/yolov7-v0.1", | |
| ], | |
| default="alshimaa/model_baseline", | |
| label="Model", | |
| ) | |
| #gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size") | |
| #gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"), | |
| #gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold") | |
| ] | |
| outputs = gr.outputs.Image(type="filepath", label="Output Image") | |
| title = "Smart Environmental Eye (SEE)" | |
| examples = [['image1.jpg.', 'alshimaa/model_baseline', 640, 0.25, 0.45], ['image2.jpg', 'alshimaa/model_baseline', 640, 0.25, 0.45], ['image3.jpg', 'alshimaa/model_baseline', 640, 0.25, 0.45]] | |
| demo_app = gr.Interface( | |
| fn=yolov7_inference, | |
| inputs=inputs, | |
| outputs=outputs, | |
| title=title, | |
| examples=examples, | |
| cache_examples=True, | |
| theme='huggingface', | |
| ) | |
| demo_app.launch(debug=True, enable_queue=True) | |