feat: bounding boxes on bird body

app/boxes_define.py

@@ -0,0 +1,23 @@
+import geopandas as gpd
+from shapely.geometry import box
+
+bounding_boxes = [
+    # 'Head incl. eyes',
+    box(250, 375, 350, 500),
+    # 'Beak and mouth region',
+    box(200, 450, 250, 500),
+    # 'Feathers/Wings', 
+    box(10, 10, 50, 50), 
+    # 'Legs', 
+    box(325, 575, 450, 675),
+    # 'Body'
+    box(500, 500, 500, 500)
+]
+
+# Create a GeoDataFrame from these boxes
+gdf = gpd.GeoDataFrame({'geometry': bounding_boxes, 
+                        'name': ['Head incl. eyes',
+                                 'Beak and mouth region',
+                                 'Feathers/Wings', 
+                                 'Legs', 
+                                 'Body']})

app/boxes_map.py

@@ -0,0 +1,26 @@
+from PIL import Image, ImageDraw, ImageFont
+
+from boxes_define import gdf
+
+# Function to draw the bounding boxes on the image
+def draw_bounding_boxes(image_path, gdf):
+    image = Image.open(image_path+'bird.png').convert("RGB")
+    # Convert the image to an editable format
+    draw = ImageDraw.Draw(image)
+
+    # Optional: Load a font (requires a TTF file)
+    try:
+        font = ImageFont.truetype("arial.ttf", 15)
+    except IOError:
+        font = ImageFont.load_default()
+
+    # Draw each bounding box on the image
+    for _, row in gdf.iterrows():
+        xmin, ymin, xmax, ymax = row['geometry'].bounds
+        draw.rectangle([xmin, ymin, xmax, ymax], outline="red", width=2)
+        draw.text((xmin, ymin-10), row['name'], fill="red", font=font)
+
+    image.save(image_path+'bird_boxed.png', "PNG")
+
+if __name__ == "__main__":
+    draw_bounding_boxes('assets/images/', gdf)

app/main.py

@@ -38,6 +38,71 @@ with gr.Blocks(theme=theme, css=css) as demo:
                 #to submit it
                 submit_location = gr.Button("Get GPS Coordinates", visible=True, interactive=True, scale=3)
                 submit_location.click(get_location, inputs=[location], outputs=[identified_location])
+    
+    # ---------------------------------------------------------
+    # ---------------------------------------------------------
+    # ---------------------------------------------------------
+
+    import random
+    import numpy as np  
+
+    section_labels = [
+        "apple",
+        "banana",
+        "carrot",
+        "donut",
+        "eggplant",
+        "fish",
+        "grapes",
+        "hamburger",
+        "ice cream",
+        "juice",
+    ]
+
+    with gr.Row():
+        num_boxes = gr.Slider(0, 5, 2, step=1, label="Number of boxes")
+        num_segments = gr.Slider(0, 5, 1, step=1, label="Number of segments")
+
+    with gr.Row():
+        img_input = gr.Image()
+        img_output = gr.AnnotatedImage(
+            color_map={"banana": "#a89a00", "carrot": "#ffae00"}
+        )
+
+    section_btn = gr.Button("Identify Sections")
+    selected_section = gr.Textbox(label="Selected Section")
+
+    def section(img, num_boxes, num_segments):
+        sections = []
+        for a in range(num_boxes):
+            x = random.randint(0, img.shape[1])
+            y = random.randint(0, img.shape[0])
+            w = random.randint(0, img.shape[1] - x)
+            h = random.randint(0, img.shape[0] - y)
+            sections.append(((x, y, x + w, y + h), section_labels[a]))
+        for b in range(num_segments):
+            x = random.randint(0, img.shape[1])
+            y = random.randint(0, img.shape[0])
+            r = random.randint(0, min(x, y, img.shape[1] - x, img.shape[0] - y))
+            mask = np.zeros(img.shape[:2])
+            for i in range(img.shape[0]):
+                for j in range(img.shape[1]):
+                    dist_square = (i - y) ** 2 + (j - x) ** 2
+                    if dist_square < r**2:
+                        mask[i, j] = round((r**2 - dist_square) / r**2 * 4) / 4
+            sections.append((mask, section_labels[b + num_boxes]))
+        return (img, sections)
+
+    section_btn.click(section, [img_input, num_boxes, num_segments], img_output)
+
+    def select_section(evt: gr.SelectData):
+        return section_labels[evt.index]
+
+    img_output.select(select_section, None, selected_section)
+
+    # ---------------------------------------------------------
+    # ---------------------------------------------------------
+    # ---------------------------------------------------------
 
     # ---------------------------------------------------------
     # Dead and Wounded Buttons

app/select_bird.py

@@ -0,0 +1,37 @@
+import gradio as gr
+# from gradio_image_prompter import ImagePrompter
+from typing import List
+from shapely.geometry import Point
+
+from boxes_define import gdf
+
+# Function to find the matching bounding box for a given point and return the image with boxes
+def find_bounding_box(evt: gr.SelectData, img):
+    x, y = evt.index[0], evt.index[1]
+    point = Point(x, y)
+    match = gdf[gdf.contains(point)]
+    
+    if not match.empty:
+        matched_box = match.iloc[0]['name']
+    else:
+        matched_box = "No bounding box found"
+    return matched_box
+
+
+# Gradio app
+with gr.Blocks() as demo:
+    # Draw bounding boxes on the image
+    
+    img_with_boxes = gr.Image(value='assets/images/bird_boxed.png', label=None)
+    
+    bbox_label = gr.Label()
+
+    img_with_boxes.select(find_bounding_box, 
+                     inputs=[img_with_boxes], 
+                     outputs=[bbox_label])
+
+
+  
+demo.launch(server_name="0.0.0.0")
+
+

requirements.txt

@@ -1,2 +1,4 @@
 gradio
-geopy
+geopy
+geopandas
+pillow