Add initial demo with basic enhancements

README.md

@@ -1,13 +1,11 @@
 ---
 title: Kornia Image Enhancement
-emoji: 📈
+emoji: 🪄
 colorFrom: red
 colorTo: purple
-sdk: gradio
+sdk: green
 sdk_version: 2.9.0
 app_file: app.py
 pinned: false
 license: apache-2.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import cv2
+
+import torch
+import kornia as K
+
+def load_torch_image(fname):
+    img = K.image_to_tensor(fname, False).float() / 255.
+    img = K.color.bgr_to_rgb(img)
+    return img
+
+
+def enhance(file, brightness, contrast, saturation, gamma, hue):
+    fname = file.name
+    im = cv2.imread(fname)                 
+    img = load_torch_image(im)
+
+    x_out: torch.Tensor = K.enhance.adjust_brightness(img, float(brightness))
+    x_out = K.enhance.adjust_contrast(x_out, float(contrast))
+    x_out = K.enhance.adjust_saturation(x_out, float(saturation))
+    x_out = K.enhance.adjust_gamma(x_out, float(gamma))
+    x_out = K.enhance.adjust_hue(x_out, float(hue))
+
+    return K.utils.tensor_to_image(x_out)
+
+
+examples = [
+    ["examples/ninja_turtles.jpg", 0, 1, 1, 1, 0],
+    ["examples/kitty.jpg", 0, 1, 1, 1, 0],
+]
+
+iface = gr.Interface(
+    enhance,
+    [
+        gr.inputs.Image(type="file"),
+        gr.inputs.Slider(minimum=0, maximum=1, step=0.1, default=0, label="Brightness"),
+        gr.inputs.Slider(minimum=0, maximum=4, step=0.1, default=1, label="Contrast"),
+        gr.inputs.Slider(minimum=0, maximum=4, step=0.1, default=1, label="Saturation"),
+        gr.inputs.Slider(minimum=0, maximum=1, step=0.1, default=1, label="Gamma"),
+        gr.inputs.Slider(minimum=0, maximum=4, step=0.1, default=0, label="Hue"),
+    ],
+    "image",
+    examples=examples,
+    live=True
+)
+
+iface.launch()

packages.txt

@@ -0,0 +1 @@
+python3-opencv

requirements.txt

@@ -0,0 +1,3 @@
+kornia
+opencv-python
+torch