Create app.py

This is the application file for gradio

app.py

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+import gradio as gr
+import supervision as sv
+from ultralytics import YOLO
+import os #added for cache_examples
+from PIL import Image, ImageColor
+import numpy as np
+
+def load_model(img):
+  # Load model, get results and return detections/labels
+  model = YOLO('yolov8s-seg.pt')
+  result = model(img, verbose=False, imgsz=1280)[0]
+  detections = sv.Detections.from_ultralytics(result)
+  labels = [
+            f"{model.model.names[class_id]} {confidence:.2f}"
+            for class_id, confidence in zip(detections.class_id, detections.confidence)
+           ]
+
+  return detections, labels
+
+def calculate_crop_dim(a,b):
+  #Calculates the crop dimensions of the image resultant
+  if a>b:
+    width= a
+    height = a
+  else:
+    width = b
+    height = b
+
+  return width, height
+
+def annotator(img,annotators,colorbb,colormask,colorellipse,colorbc,colorcir,colorlabel):
+
+    """
+    Function that changes the color of annotators
+    Args:
+        annotators: Icon whose color needs to be changed.
+        color: Chosen color with which to edit the input icon in Hex.
+        img: Input image is numpy matrix in BGR.
+    Returns:
+        annotators: annotated image
+    """
+
+
+
+    img = img[...,::-1].copy() # BGR to RGB using numpy
+
+
+    detections, labels = load_model(img)
+
+
+    if "Blur" in annotators:
+        # Apply Blur
+        blur_annotator = sv.BlurAnnotator()
+        img = blur_annotator.annotate(img, detections=detections)
+
+    if "BoundingBox" in annotators:
+        # Draw Bounding box
+        box_annotator = sv.BoundingBoxAnnotator(sv.Color.from_hex(str(colorbb)))
+        img = box_annotator.annotate(img, detections=detections)
+
+    if "Mask" in annotators:
+        # Draw Mask
+        mask_annotator = sv.MaskAnnotator(sv.Color.from_hex(str(colormask)))
+        img = mask_annotator.annotate(img, detections=detections)
+
+    if "Ellipse" in annotators:
+        # Draw ellipse
+        ellipse_annotator = sv.EllipseAnnotator(sv.Color.from_hex(str(colorellipse)))
+        img = ellipse_annotator.annotate(img, detections=detections)
+
+    if "BoxCorner" in annotators:
+        # Draw Box corner
+        corner_annotator = sv.BoxCornerAnnotator(sv.Color.from_hex(str(colorbc)))
+        img = corner_annotator.annotate(img, detections=detections)
+
+
+    if "Circle" in annotators: 
+        # Draw circle
+        circle_annotator = sv.CircleAnnotator(sv.Color.from_hex(str(colorcir)))
+        img = circle_annotator.annotate(img, detections=detections)
+
+    if "Label" in annotators:
+        # Draw Label
+        label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
+        label_annotator = sv.LabelAnnotator(sv.Color.from_hex(str(colorlabel)))
+        img = label_annotator.annotate(img, detections=detections, labels=labels)
+
+
+
+    #crop image for the largest possible square
+    res_img = Image.fromarray(img)
+    print(type(res_img))
+
+    x=0
+    y=0
+
+
+    print("size of the pil im=", res_img.size)
+    (v1,v2) = res_img.size
+    width, height = calculate_crop_dim(v1, v2)
+    print(width, height)
+    my_img = np.array(res_img)
+
+    crop_img = my_img[y:y+height, x:x+width]
+    print(type(crop_img))
+
+    return crop_img[...,::-1].copy() # BGR to RGB using numpy
+
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue=gr.themes.colors.purple)
+    .set(
+      button_primary_background_fill="*primary_600",
+      button_primary_background_fill_hover="*primary_700",
+      checkbox_label_background_fill_selected="*primary_600",
+      checkbox_background_color_selected="*primary_400",
+    )) as demo:
+    gr.Markdown("""# Supervision Annotators""")
+    annotators = gr.CheckboxGroup(choices=["BoundingBox", "Mask", "Ellipse", "BoxCorner", "Circle", "Label", "Blur"], value=["BoundingBox", "Mask"], label="Select Annotators:")
+
+    with gr.Accordion("**Color Picker**"):
+      with gr.Row():
+        with gr.Column():
+          colorbb = gr.ColorPicker(value="#A351FB",label="BoundingBox")
+        with gr.Column():
+          colormask = gr.ColorPicker(value="#A351FB",label="Mask")
+        with gr.Column():
+          colorellipse = gr.ColorPicker(value="#A351FB",label="Ellipse")
+        with gr.Column():
+          colorbc = gr.ColorPicker(value="#A351FB",label="BoxCorner")
+        with gr.Column():
+          colorcir = gr.ColorPicker(value="#A351FB",label="Circle")
+        with gr.Column():
+          colorlabel = gr.ColorPicker(value="#A351FB",label="Label")
+    
+    with gr.Row():
+      with gr.Column():
+        with gr.Tab("Input image"):
+          image_input = gr.Image(type="numpy", show_label=False)
+      with gr.Column():
+        with gr.Tab("Result image"):
+          image_output = gr.Image(type="numpy", show_label=False)
+    image_button = gr.Button(value="Annotate it!", variant="primary")
+
+    image_button.click(annotator, inputs=[image_input,annotators,colorbb,colormask,colorellipse,colorbc,colorcir,colorlabel], outputs=image_output)
+
+    gr.Markdown("## Image Examples")
+    gr.Examples(
+        examples=[os.path.join(os.path.abspath(''), "city.jpg"), 
+                  os.path.join(os.path.abspath(''), "household.jpg"), 
+                  os.path.join(os.path.abspath(''), "industry.jpg"),
+                  os.path.join(os.path.abspath(''), "retail.jpg"),
+                  os.path.join(os.path.abspath(''), "aerodefence.jpg")],
+        inputs=image_input,
+        outputs=image_output,
+        fn=annotator,
+        cache_examples=False,
+    )
+
+
+demo.launch(debug=False)