Duplicate from nihalbaig/BD-Vehicle-Detection

Co-authored-by: Mirza Nihal Baig <[email protected]>

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README.md

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+---
+title: BD Vehicle Detection
+emoji: 🌍
+colorFrom: pink
+colorTo: blue
+sdk: gradio
+sdk_version: 3.19.1
+app_file: app.py
+pinned: false
+duplicated_from: nihalbaig/BD-Vehicle-Detection
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+import yolov7
+
+
+# Images
+#torch.hub.download_url_to_file('https://raw.githubusercontent.com/nihalbaig0/BD-Vehicle-Detection/main/images/bondor_to_kodomtoli.jpg', 'bondor_to_kodomtoli.jpg')
+#torch.hub.download_url_to_file('https://raw.githubusercontent.com/nihalbaig0/BD-Vehicle-Detection/main/images/lamabazar_to_versitygate.jpg', 'lamabazar_to_versitygate.jpg')
+    
+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=[
+            "nihalbaig/yolov7",
+            
+        ],
+        default="nihalbaig0/yolov7",
+        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 = "Project-350: BD Vehicle Detection for Autonomous Vehicle"
+
+#examples = [['bondor_to_kodomtoli.jpg', 'nihalbaig0/yolov7', 640, 0.25, 0.45], ['lamabazar_to_versitygate.jpg', 'nihalbaig0/yolov7', 640, 0.25, 0.45]]
+demo_app = gr.Interface(
+    fn=yolov7_inference,
+    inputs=inputs,
+    outputs=outputs,
+    title=title,
+    #examples=examples,
+    cache_examples=True,
+    theme='darkhuggingface',
+)
+demo_app.launch(debug=True, enable_queue=True)

requirements.txt

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+torch
+yolov7detect