Add example images and update SAM2 settings

app.py

@@ -166,11 +166,6 @@ Upload a plant leaf image to detect disease regions using AI.
                 )
 
                 with gr.Row():
-                    leaf_seg_checkbox = gr.Checkbox(
-                        value=True,
-                        label="Isolate leaf (SAM2)",
-                        info="Segment leaf before detection to reduce false positives"
-                    )
                     confidence_slider = gr.Slider(
                         minimum=0.1,
                         maximum=0.9,
@@ -179,6 +174,12 @@ Upload a plant leaf image to detect disease regions using AI.
                         label="Confidence Threshold"
                     )
 
+                gr.Markdown("**SAM2 Segmentation**: Enable to improve detection accuracy by isolating the leaf and generating precise disease masks instead of bounding boxes.")
+                leaf_seg_checkbox = gr.Checkbox(
+                    value=False,
+                    label="Enable SAM2 segmentation"
+                )
+
                 detect_btn = gr.Button("Detect Disease", variant="primary", size="lg")
 
             with gr.Column():
@@ -192,6 +193,24 @@ Upload a plant leaf image to detect disease regions using AI.
                     value="Upload an image and click 'Detect Disease' to see results."
                 )
 
+        # Example images
+        gr.Markdown("### Example Images")
+        gr.Markdown("Click an example image to load it:")
+
+        example_images = [
+            ["examples/img1.png"],
+            ["examples/img2.png"],
+            ["examples/img3.png"],
+            ["examples/img4.png"],
+            ["examples/img5.png"],
+        ]
+
+        gr.Examples(
+            examples=example_images,
+            inputs=[input_image],
+            label="Select an example"
+        )
+
         # Event handler
         detect_btn.click(
             fn=detect_disease,

models/severity_classifier/best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8b8a09bf95bddab9421204e9ca9c2b085e5b941e9532ddccef526801b52eeeaa
+size 48579306

src/leaf_segmenter.py

@@ -7,7 +7,7 @@ from backgrounds before disease detection.
 
 import numpy as np
 from PIL import Image
-from typing import Optional, Tuple
+from typing import Optional, Tuple, List
 import torch
 
 
@@ -50,6 +50,7 @@ class SAM2LeafSegmenter:
 
         self.model = None
         self.predictor = None
+        self.mask_generator = None
 
     def load_model(self):
         """Load SAM2 model."""
@@ -68,6 +69,27 @@ class SAM2LeafSegmenter:
         self.predictor = SAM2ImagePredictor(self.model)
         print("SAM2 model loaded.")
 
+    def load_mask_generator(self):
+        """Load SAM2 automatic mask generator for multi-object segmentation."""
+        self.load_model()
+
+        if self.mask_generator is not None:
+            return
+
+        from sam2.automatic_mask_generator import SAM2AutomaticMaskGenerator
+
+        print("Initializing SAM2 automatic mask generator...")
+        self.mask_generator = SAM2AutomaticMaskGenerator(
+            model=self.model,
+            points_per_side=32,
+            points_per_batch=64,
+            pred_iou_thresh=0.7,
+            stability_score_thresh=0.92,
+            crop_n_layers=1,
+            min_mask_region_area=500,
+        )
+        print("SAM2 mask generator ready.")
+
     def segment_leaf(
         self,
         image: Image.Image,