Spaces:
Sleeping
Sleeping
Taha Razzaq
commited on
Commit
·
92494bc
1
Parent(s):
37ea0b9
errors fixed + preview updated
Browse files
app.py
CHANGED
@@ -1,23 +1,34 @@
|
|
1 |
-
import keras
|
2 |
-
import numpy as np
|
3 |
import gradio as gr
|
4 |
-
from tibblingai import wta
|
5 |
from PIL import Image, ImageOps
|
6 |
-
import
|
7 |
-
|
8 |
-
|
9 |
def load_sample_images():
|
10 |
sample_paths = ["sample1.jpg", "sample2.jpg"] # Must be in the same folder as your script
|
11 |
original_imgs = [Image.open(path) for path in sample_paths]
|
12 |
processed_imgs = [process_image(path) for path in sample_paths]
|
13 |
return gr.update(visible=True, value=original_imgs), gr.update(visible=True, value=processed_imgs)
|
14 |
|
|
|
|
|
15 |
# Image processing function (you can replace this)
|
16 |
def process_image(img: Image.Image) -> Image.Image:
|
17 |
-
|
18 |
-
|
19 |
-
|
20 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
21 |
|
22 |
# Function to process uploaded images
|
23 |
def process_images(images):
|
@@ -28,8 +39,9 @@ def process_images(images):
|
|
28 |
processed_imgs = []
|
29 |
|
30 |
for img in images:
|
31 |
-
|
32 |
-
|
|
|
33 |
|
34 |
return gr.update(visible=True, value=original_imgs), gr.update(visible=True, value=processed_imgs)
|
35 |
|
@@ -60,4 +72,4 @@ with gr.Blocks() as demo:
|
|
60 |
|
61 |
# example_files = [["sample1.jpg", "sample2.jpg"], ["sample2.jpg"]]
|
62 |
# gr.Examples(examples=example_files, inputs=[file_input], label="Try one of our example samples")
|
63 |
-
demo.launch()
|
|
|
|
|
|
|
1 |
import gradio as gr
|
|
|
2 |
from PIL import Image, ImageOps
|
3 |
+
import numpy as np
|
4 |
+
import matplotlib.pyplot as plt # needed for plt.imread
|
|
|
5 |
def load_sample_images():
|
6 |
sample_paths = ["sample1.jpg", "sample2.jpg"] # Must be in the same folder as your script
|
7 |
original_imgs = [Image.open(path) for path in sample_paths]
|
8 |
processed_imgs = [process_image(path) for path in sample_paths]
|
9 |
return gr.update(visible=True, value=original_imgs), gr.update(visible=True, value=processed_imgs)
|
10 |
|
11 |
+
|
12 |
+
|
13 |
# Image processing function (you can replace this)
|
14 |
def process_image(img: Image.Image) -> Image.Image:
|
15 |
+
# Read image using matplotlib
|
16 |
+
img_np = plt.imread(img)
|
17 |
+
if img_np.ndim == 3 and img_np.shape[2] > 3:
|
18 |
+
img_np = img_np[:, :, :3]
|
19 |
+
|
20 |
+
# Convert to grayscale for original image display
|
21 |
+
gray_img = ImageOps.grayscale(Image.fromarray((img_np * 255).astype(np.uint8)))
|
22 |
+
|
23 |
+
# Run your WTA processing (dummy if not available)
|
24 |
+
# Replace this line with actual WTA processing
|
25 |
+
img_tensor = wta.wta(img_np).numpy() # Assuming returns shape (1, H, W)
|
26 |
+
|
27 |
+
# Convert processed image to inferno colormap
|
28 |
+
inferno_colored = plt.cm.inferno(img_tensor[0])
|
29 |
+
inferno_img = Image.fromarray((inferno_colored[:, :, :3] * 255).astype(np.uint8))
|
30 |
+
|
31 |
+
return gray_img, inferno_img
|
32 |
|
33 |
# Function to process uploaded images
|
34 |
def process_images(images):
|
|
|
39 |
processed_imgs = []
|
40 |
|
41 |
for img in images:
|
42 |
+
original_gray_scale_img, inferno_img = process_image(img)
|
43 |
+
original_imgs.append(original_gray_scale_img)
|
44 |
+
processed_imgs.append(inferno_img)
|
45 |
|
46 |
return gr.update(visible=True, value=original_imgs), gr.update(visible=True, value=processed_imgs)
|
47 |
|
|
|
72 |
|
73 |
# example_files = [["sample1.jpg", "sample2.jpg"], ["sample2.jpg"]]
|
74 |
# gr.Examples(examples=example_files, inputs=[file_input], label="Try one of our example samples")
|
75 |
+
demo.launch(debug=True)
|