Add negative prompts to segment-anything. (#1000)

candle-examples/examples/segment-anything/main.rs

@@ -27,10 +27,16 @@ struct Args {
     #[arg(long)]
     generate_masks: bool,
 
-    /// List of x,y coordinates, between 0 and 1 (0.5 is at the middle of the image).
+    /// List of x,y coordinates, between 0 and 1 (0.5 is at the middle of the image). These points
+    /// should be part of the generated mask.
     #[arg(long)]
     point: Vec<String>,
 
+    /// List of x,y coordinates, between 0 and 1 (0.5 is at the middle of the image). These points
+    /// should not be part of the generated mask and should be part of the background instead.
+    #[arg(long)]
+    neg_point: Vec<String>,
+
     /// The detection threshold for the mask, 0 is the default value, negative values mean a larger
     /// mask, positive makes the mask more selective.
     #[arg(long, default_value_t = 0.)]
@@ -107,16 +113,17 @@ pub fn main() -> anyhow::Result<()> {
             )?;
         }
     } else {
-        let points = args
-            .point
-            .iter()
-            .map(|point| {
+        let iter_points = args.point.iter().map(|p| (p, true));
+        let iter_neg_points = args.neg_point.iter().map(|p| (p, false));
+        let points = iter_points
+            .chain(iter_neg_points)
+            .map(|(point, b)| {
                 use std::str::FromStr;
                 let xy = point.split(',').collect::<Vec<_>>();
                 if xy.len() != 2 {
                     anyhow::bail!("expected format for points is 0.4,0.2")
                 }
-                Ok((f64::from_str(xy[0])?, f64::from_str(xy[1])?))
+                Ok((f64::from_str(xy[0])?, f64::from_str(xy[1])?, b))
             })
             .collect::<anyhow::Result<Vec<_>>>()?;
         let start_time = std::time::Instant::now();
@@ -158,15 +165,15 @@ pub fn main() -> anyhow::Result<()> {
                 }
             }
         }
-        for (x, y) in points {
+        for (x, y, b) in points {
             let x = (x * img.width() as f64) as i32;
             let y = (y * img.height() as f64) as i32;
-            imageproc::drawing::draw_filled_circle_mut(
-                &mut img,
-                (x, y),
-                3,
-                image::Rgba([255, 0, 0, 200]),
-            );
+            let color = if b {
+                image::Rgba([255, 0, 0, 200])
+            } else {
+                image::Rgba([0, 255, 0, 200])
+            };
+            imageproc::drawing::draw_filled_circle_mut(&mut img, (x, y), 3, color);
         }
         img.save("sam_merged.jpg")?
     }

candle-transformers/src/models/segment_anything/sam.rs

@@ -130,7 +130,7 @@ impl Sam {
     pub fn forward(
         &self,
         img: &Tensor,
-        points: &[(f64, f64)],
+        points: &[(f64, f64, bool)],
         multimask_output: bool,
     ) -> Result<(Tensor, Tensor)> {
         let (_c, original_h, original_w) = img.dims3()?;
@@ -150,12 +150,17 @@ impl Sam {
         Ok((mask, iou))
     }
 
+    /// Generate the mask and IOU predictions from some image embeddings and prompt.
+    ///
+    /// The prompt is specified as a list of points `(x, y, b)`. `x` and `y` are the point
+    /// coordinates (between 0 and 1) and `b` is `true` for points that should be part of the mask
+    /// and `false` for points that should be part of the background and so excluded from the mask.
     pub fn forward_for_embeddings(
         &self,
         img_embeddings: &Tensor,
         original_h: usize,
         original_w: usize,
-        points: &[(f64, f64)],
+        points: &[(f64, f64, bool)],
         multimask_output: bool,
     ) -> Result<(Tensor, Tensor)> {
         let image_pe = self.prompt_encoder.get_dense_pe()?;
@@ -165,14 +170,18 @@ impl Sam {
             let n_points = points.len();
             let xys = points
                 .iter()
-                .flat_map(|(x, y)| {
+                .flat_map(|(x, y, _b)| {
                     let x = (*x as f32) * (original_w as f32);
                     let y = (*y as f32) * (original_h as f32);
                     [x, y]
                 })
                 .collect::<Vec<_>>();
+            let labels = points
+                .iter()
+                .map(|(_x, _y, b)| if *b { 1f32 } else { 0f32 })
+                .collect::<Vec<_>>();
             let points = Tensor::from_vec(xys, (1, n_points, 2), img_embeddings.device())?;
-            let labels = Tensor::ones((1, n_points), DType::F32, img_embeddings.device())?;
+            let labels = Tensor::from_vec(labels, (1, n_points), img_embeddings.device())?;
             Some((points, labels))
         };
         let points = points.as_ref().map(|(x, y)| (x, y));

candle-wasm-examples/segment-anything/src/bin/m.rs

@@ -94,7 +94,7 @@ impl Model {
             &embeddings.data,
             embeddings.height as usize,
             embeddings.width as usize,
-            &[(x, y)],
+            &[(x, y, true)],
             false,
         )?;
         let iou = iou_predictions.flatten(0, 1)?.to_vec1::<f32>()?[0];