interactive-pipe template

app.py

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+from interactive_pipe import interactive_pipeline, interactive, Image
+from typing import Tuple
+import numpy as np
+
+
+# Processing blocks
+# -----------------
+def processing_block(
+    inp: np.ndarray,
+    amplify: float = 1.,
+    context: dict = {}
+) -> np.ndarray:
+    context["amplify"] = amplify
+    return amplify*inp
+
+
+# Pipeline definition
+# -------------------
+
+def pipe(inp: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
+    out = processing_block(inp)
+    return inp, out
+
+# Add interactivity to the processing blocks
+# ------------------------------------------
+
+
+def add_controls() -> None:
+    interactive(
+        amplify=(0.5, [0., 1.], "Amplify")
+    )(processing_block)
+
+# Add interactivity to the processing blocks
+# ------------------------------------------
+
+
+def launch(img: np.ndarray, backend: str = "gradio"):
+    add_controls()
+    pipe_interactive = interactive_pipeline(
+        gui=backend,
+        markdown_description=markdown_description
+    )(pipe)
+    pipe_interactive(img)
+
+
+if __name__ == "__main__":
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-b", "--backend", default="gradio",
+                        choices=["gradio", "qt", "mpl"], type=str)
+    parser.add_argument(
+        "-d", "--debug", action="store_true",
+        help="Debug mode (to tune difficulty and tolerance)"
+    )
+    args = parser.parse_args()
+    markdown_description = "# Code to build this app on gradio \n\n"
+    markdown_description += "```python\n"+open(__file__, 'r').read()+"```"
+    img = Image.load_image("sample.jpg")
+    launch(img, backend=args.backend)

requirements.txt

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+interactive-pipe>=0.8.3