initial files

.devcontainer/devcontainer.json

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+{
+	"name": "Existing Dockerfile",
+	"build": {
+		// Sets the run context to one level up instead of the .devcontainer folder.
+		"context": "..",
+		// Update the 'dockerFile' property if you aren't using the standard 'Dockerfile' filename.
+		"dockerfile": "../Dockerfile"
+	},
+	"customizations": {
+		"vscode": {
+			"extensions": [
+				"ms-azuretools.vscode-docker",
+				"ms-python.python",
+				"ms-python.debugpy",
+				"ms-vscode.makefile-tools",
+				"ms-toolsai.jupyter",
+				"ms-toolsai.datawrangler",
+				"k--kato.intellij-idea-keybindings"
+			]
+		}
+	}
+}

.gitattributes

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-*tfevents* filter=lfs diff=lfs merge=lfs -text
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
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+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.13-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get upgrade -y && \ 
+apt-get install -y build-essential git nano cmake libzbar0 libgl1 && \
+pip install --upgrade pip
+
+# Install UV package manager
+RUN pip install uv
+
+# Copy requirements file
+COPY requirements.txt .
+
+# Install dependencies
+RUN uv pip install -r requirements.txt --system
+
+

README.md

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----
-title: Test Segmentation
-emoji: 🚀
-colorFrom: gray
-colorTo: green
-sdk: gradio
-sdk_version: 5.30.0
-app_file: app.py
-pinned: false
-license: mit
-short_description: Test Segmentation
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Test Segmentation
+emoji: 🚀
+colorFrom: gray
+colorTo: green
+sdk: gradio
+sdk_version: 5.30.0
+app_file: app.py
+pinned: false
+license: mit
+short_description: Test Segmentation
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from ultralytics import YOLO
+import cv2
+import numpy as np
+from PIL import Image
+
+# Load the YOLO model with the provided weights
+model = YOLO("yolo_weigths.pt")
+
+def segment_image(input_image):
+    """
+    This function takes an image as input and, using a YOLO model, returns the detected objects in the image.
+
+    Args:
+        input_image: The image to be segmented.
+
+    Returns:
+        annotated_img: The annotated image with the detected objects.
+    """
+    
+    # Convert gradio image to numpy array if it's not already
+    if isinstance(input_image, np.ndarray):
+        img = input_image
+    else:
+        img = np.array(input_image)
+    
+    # Run inference
+    results = model(img)
+    
+    # Get the annotated image from results
+    annotated_img = results[0].plot()
+    
+    return annotated_img
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=segment_image,
+    inputs=gr.Image(),
+    outputs=gr.Image(),
+    title="YOLO Image Segmentation",
+    description="Upload an image to run object detection and segmentation using YOLO."
+)
+
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)

requirements.txt

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+numpy
+opencv-python
+matplotlib
+loguru
+ultralytics
+gradio[mcp]
+
+
+
+

yolo_weigths.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5d0d7d575eaf028a16fbfd349ba5b29656e2c8180475cb3ee43ced94a69b0826
+size 124842714