Initial Commit

app.py

@@ -3,7 +3,6 @@ import matplotlib.pyplot as plt
 import cv2
 import torch
 from segment_anything import sam_model_registry, SamPredictor
-from preprocess import show_mask, show_points, show_box
 import gradio as gr
 
 sam_checkpoint = {
@@ -37,6 +36,9 @@ def inference(image, input_label, model_choice):
     mask = masks[0]
     image2 = image.copy()
     image2[mask, 0] = 255
+    image2[int(input_label['label'].split(',')[0])-10:int(input_label['label'].split(',')[0])+10,
+           int(input_label['label'].split(',')[1])-10:int(input_label['label'].split(',')[1])+10,
+           2] = 255
     return image2
 
 

preprocess.py

@@ -1,23 +0,0 @@
-import numpy as np
-import matplotlib.pyplot as plt
-import cv2
-
-def show_mask(mask, ax, random_color=False):
-    if random_color:
-        color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0)
-    else:
-        color = np.array([30/255, 144/255, 255/255, 0.6])
-    h, w = mask.shape[-2:]
-    mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1)
-    ax.imshow(mask_image)
-    
-def show_points(coords, labels, ax, marker_size=375):
-    pos_points = coords[labels==1]
-    neg_points = coords[labels==0]
-    ax.scatter(pos_points[:, 0], pos_points[:, 1], color='green', marker='*', s=marker_size, edgecolor='white', linewidth=1.25)
-    ax.scatter(neg_points[:, 0], neg_points[:, 1], color='red', marker='*', s=marker_size, edgecolor='white', linewidth=1.25)   
-    
-def show_box(box, ax):
-    x0, y0 = box[0], box[1]
-    w, h = box[2] - box[0], box[3] - box[1]
-    ax.add_patch(plt.Rectangle((x0, y0), w, h, edgecolor='green', facecolor=(0,0,0,0), lw=2))