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README.md

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 ---
-title: Lobaarm
-emoji: 📉
-colorFrom: purple
-colorTo: green
-sdk: static
-pinned: false
-license: apache-2.0
+license: mit
+language:
+- en
+metrics:
+- precision
+pipeline_tag: object-detection
+tags:
+- Classification
+- YoloV8
+- Guns Detection
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## Model Details
+YoloV8n 3M parameters model for Guns Detection, trained on 16k images
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Shared by [optional]:** Karun Sharma
+- **License:** MIT
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Demo:** https://huggingface.co/spaces/Zcket/Gun_Detect
+
+## Uses
+Can be used to detect presenece of Guns in images for Moderation.
+
+
+
+### Downstream Use [optional]
+Classes of Arms/Guns(Pistols, Grenades)
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```py
+from ultralytics import YOLO
+
+model = YOLO('best.pt')
+
+results = model(['im1.jpg', 'im2.jpg'])  # return a list of Results objects
+
+# Process results list
+for result in results:
+    boxes = result.boxes  # Boxes object for bounding box outputs
+    masks = result.masks  # Masks object for segmentation masks outputs
+    keypoints = result.keypoints  # Keypoints object for pose outputs
+    probs = result.probs  # Probs object for classification outputs
+    result.show()  # display to screen
+    result.save(filename='result.jpg')  # save to disk
+```
+

app.py

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+from ultralytics import YOLO
+
+model = YOLO('best.pt')
+
+image_path = input("Enter image path: ")
+results = model(image_path, device = 0, amp = 'True')  # return a list of Results objects
+
+print(results)

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7741299264b8915ef70c8eadd9e443bb77dd2dc3756012fc933d0e6d023fe913
+size 132

requirements.txt

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+torch
+ultralytics

yolov8_background1k_best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:34ab3b563e937680ad12b5a382b086b9e6a79c1bc950e70106560b2ad3a3e2aa
+size 133