feat: Add app file

app.py

@@ -0,0 +1,49 @@
+import numpy as np
+import cv2
+
+import gradio as gr
+from huggingface_hub import hf_hub_download
+
+from scgan.config import Config
+from scgan.generate_images import ImgGenerator
+
+
+def download_weights(repo_id):
+    char_map_path = hf_hub_download(repo_id, "char_map.pkl")
+    weights_path = hf_hub_download(repo_id, "model_checkpoint_epoch_200.pth.tar")
+    return char_map_path, weights_path
+
+
+def get_text_from_image(img):
+    COLOR_MIN = np.array([0, 0, 0],np.uint8)
+    COLOR_MAX = np.array([250,250,160],np.uint8)
+
+    img = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
+    text_mask = cv2.inRange(img, COLOR_MIN, COLOR_MAX).astype(bool)
+    img = cv2.cvtColor(img, cv2.COLOR_HSV2RGB)
+
+    bg = np.ones(img.shape, dtype=np.uint8) * 255
+    bg[text_mask] = img[text_mask]
+    return bg
+
+
+def predict(text):
+    imgs, texts = GENERATOR.generate(word_list=[text])
+    image_on_white = get_text_from_image(imgs[0])
+    return image_on_white
+
+
+CHAR_MAP_PATH, WEIGHTS_PATH = download_weights("sberbank-ai/scrabblegan-peter")
+
+GENERATOR = ImgGenerator(
+    checkpt_path=WEIGHTS_PATH,
+    config=Config,
+    char_map_path=CHAR_MAP_PATH
+)
+
+gr.Interface(
+    predict,
+    inputs=gr.Textbox(label="Type your text to generate it on an image"),
+    outputs=gr.Image(label="Generated image"),
+    title="Peter handwritten image generation",
+).launch()