Spaces:
Runtime error
Runtime error
fix: medsam model
Browse files- app.py +22 -10
- models/{medsam_vitb.pth → medsam_vitb_best.pth} +2 -2
app.py
CHANGED
@@ -1,4 +1,3 @@
|
|
1 |
-
import os
|
2 |
import numpy as np
|
3 |
import gradio as gr
|
4 |
import torch
|
@@ -6,8 +5,9 @@ import cv2
|
|
6 |
from segment_anything import SamPredictor, sam_model_registry
|
7 |
|
8 |
# Global variables
|
|
|
9 |
OFFICIAL_CHECKPOINT = "./models/sam_vit_b_01ec64.pth"
|
10 |
-
MEDSAM_CHECKPOINT = "./models/
|
11 |
MODEL_TYPE = "vit_b"
|
12 |
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
|
13 |
|
@@ -22,6 +22,17 @@ MEDSAM.to(device=DEVICE)
|
|
22 |
MEDSAM_PREDICTOR = SamPredictor(MEDSAM)
|
23 |
|
24 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
25 |
def draw_contour(image: np.ndarray, mask: np.ndarray) -> np.ndarray:
|
26 |
# draw contour
|
27 |
contour_image = image.copy()
|
@@ -53,12 +64,12 @@ def inference(
|
|
53 |
return contour_image
|
54 |
|
55 |
|
56 |
-
def extract_object_by_event(
|
57 |
-
|
58 |
-
)
|
59 |
click_h, click_w = evt.index
|
60 |
|
61 |
-
return inference(
|
62 |
|
63 |
|
64 |
def get_coords(evt: gr.SelectData):
|
@@ -76,10 +87,11 @@ with gr.Blocks() as demo:
|
|
76 |
)
|
77 |
with gr.Row():
|
78 |
# select model
|
79 |
-
|
80 |
-
["oficial_sam", "breast-cancer-sam"],
|
81 |
-
value="oficial_sam",
|
82 |
label="Select Model",
|
|
|
|
|
|
|
83 |
)
|
84 |
|
85 |
# Segment image
|
@@ -96,7 +108,7 @@ with gr.Blocks() as demo:
|
|
96 |
with gr.Row():
|
97 |
coord_h = gr.Number(label="Mouse coords h")
|
98 |
coord_w = gr.Number(label="Mouse coords w")
|
99 |
-
input_image.select(extract_object_by_event, [input_image], output)
|
100 |
input_image.select(get_coords, None, [coord_h, coord_w])
|
101 |
|
102 |
demo.queue().launch(debug=True, enable_queue=True)
|
|
|
|
|
1 |
import numpy as np
|
2 |
import gradio as gr
|
3 |
import torch
|
|
|
5 |
from segment_anything import SamPredictor, sam_model_registry
|
6 |
|
7 |
# Global variables
|
8 |
+
MODELS = ["./models/sam_vit_b_01ec64.pth", "./models/medsam_vitb.pth"]
|
9 |
OFFICIAL_CHECKPOINT = "./models/sam_vit_b_01ec64.pth"
|
10 |
+
MEDSAM_CHECKPOINT = "./models/medsam_vitb_best.pth"
|
11 |
MODEL_TYPE = "vit_b"
|
12 |
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
|
13 |
|
|
|
22 |
MEDSAM_PREDICTOR = SamPredictor(MEDSAM)
|
23 |
|
24 |
|
25 |
+
def load_model(model_choice: int) -> SamPredictor:
|
26 |
+
"""Load model."""
|
27 |
+
print("model_choice", model_choice)
|
28 |
+
if model_choice == 0:
|
29 |
+
return SAM_PREDICTOR
|
30 |
+
elif model_choice == 1:
|
31 |
+
return MEDSAM_PREDICTOR
|
32 |
+
else:
|
33 |
+
raise ValueError("Model choice must be 0 or 1")
|
34 |
+
|
35 |
+
|
36 |
def draw_contour(image: np.ndarray, mask: np.ndarray) -> np.ndarray:
|
37 |
# draw contour
|
38 |
contour_image = image.copy()
|
|
|
64 |
return contour_image
|
65 |
|
66 |
|
67 |
+
def extract_object_by_event(model_choice: int, image: np.ndarray, evt: gr.SelectData):
|
68 |
+
"""Extract object by mouse click."""
|
69 |
+
predictor = load_model(model_choice)
|
70 |
click_h, click_w = evt.index
|
71 |
|
72 |
+
return inference(predictor, image, click_h, click_w)
|
73 |
|
74 |
|
75 |
def get_coords(evt: gr.SelectData):
|
|
|
87 |
)
|
88 |
with gr.Row():
|
89 |
# select model
|
90 |
+
model_choice = gr.Dropdown(
|
|
|
|
|
91 |
label="Select Model",
|
92 |
+
choices=[m for m in MODELS],
|
93 |
+
type="index",
|
94 |
+
interactive=True,
|
95 |
)
|
96 |
|
97 |
# Segment image
|
|
|
108 |
with gr.Row():
|
109 |
coord_h = gr.Number(label="Mouse coords h")
|
110 |
coord_w = gr.Number(label="Mouse coords w")
|
111 |
+
input_image.select(extract_object_by_event, [model_choice, input_image], output)
|
112 |
input_image.select(get_coords, None, [coord_h, coord_w])
|
113 |
|
114 |
demo.queue().launch(debug=True, enable_queue=True)
|
models/{medsam_vitb.pth → medsam_vitb_best.pth}
RENAMED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2b194d15811c1471edd68a65b19d76932f49450cb8e5f20cddae08ac142c8101
|
3 |
+
size 375063985
|