diff --git a/.gitattributes b/.gitattributes index 1097fcf8b11ceb151099bc5fb73c44045803feec..7db6dcf23696008a74af8cafcfd3d9d3595172aa 100644 --- a/.gitattributes +++ b/.gitattributes @@ -32,5 +32,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text *.zip filter=lfs diff=lfs merge=lfs -text *.zst filter=lfs diff=lfs merge=lfs -text *tfevents* filter=lfs diff=lfs merge=lfs -text -third_party filter=lfs diff=lfs merge=lfs -text -pretrained_models filter=lfs diff=lfs merge=lfs -text +**.png filter=lfs diff=lfs merge=lfs -text +**.gif filter=lfs diff=lfs merge=lfs -text +**.jpg filter=lfs diff=lfs merge=lfs -text +third_party/** filter=lfs diff=lfs merge=lfs -text +pretrained_models/** filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..17452ad75a22684fd8c44d1b8a5fbb840f56090a --- /dev/null +++ b/.gitignore @@ -0,0 +1,15 @@ +# Python byte code, etc. +__pycache__/ + +# C/C++ object files/libraries +*.o +*.so + +# macOS +**/.DS_Store + +# tmp +~* + +# third_party git +third_party/**.git \ No newline at end of file diff --git a/app.py b/app.py index e753b32d684f925459fe77f0ebf8cab328cce142..3030f15a59e640ba3c8982890618077afc4ba844 100644 --- a/app.py +++ b/app.py @@ -1,25 +1,84 @@ import gradio as gr import numpy as np - +from pathlib import Path +from matplotlib import pyplot as plt +import torch +import tempfile +import os from sam_segment import predict_masks_with_sam from lama_inpaint import inpaint_img_with_lama from utils import load_img_to_array, save_array_to_img, dilate_mask, \ show_mask, show_points +def mkstemp(suffix, dir=None): + fd, path = tempfile.mkstemp(suffix=f"{suffix}", dir=dir) + os.close(fd) + return Path(path) + + +def get_masked_img(img, point_coords): + point_labels = [1] + dilate_kernel_size = 15 + device = "cuda" if torch.cuda.is_available() else "cpu" + masks, _, _ = predict_masks_with_sam( + img, + [point_coords], + point_labels, + model_type="vit_h", + ckpt_p="pretrained_models/sam_vit_h_4b8939.pth", + device=device, + ) + masks = masks.astype(np.uint8) * 255 + + # dilate mask to avoid unmasked edge effect + if dilate_kernel_size is not None: + masks = [dilate_mask(mask, dilate_kernel_size) for mask in masks] + + figs = [] + for idx, mask in enumerate(masks): + # save the pointed and masked image + tmp_p = mkstemp(".png") + dpi = plt.rcParams['figure.dpi'] + height, width = img.shape[:2] + fig = plt.figure(figsize=(width/dpi/0.77, height/dpi/0.77)) + plt.imshow(img) + plt.axis('off') + # show_points(plt.gca(), [point_coords], point_labels, + # size=(width*0.04)**2) + # plt.savefig(tmp_p, bbox_inches='tight', pad_inches=0) + show_mask(plt.gca(), mask, random_color=False) + plt.savefig(tmp_p, bbox_inches='tight', pad_inches=0) + figs.append(fig) + plt.close() + return figs + + + with gr.Blocks() as demo: with gr.Row(): - input_img = gr.Image(label="Input") - output_img = gr.Image(label="Selected Segment") - + img = gr.Image(label="Image") + with gr.Row(label="Image with Segmentation Mask"): + img_with_mask_0 = gr.Plot() + img_with_mask_1 = gr.Plot() + img_with_mask_2 = gr.Plot() with gr.Row(): - h = gr.Number() w = gr.Number() + h = gr.Number() + + predict_mask = gr.Button("Predict Mask Using SAM") + + + def get_select_coords(evt: gr.SelectData): + return evt.index[0], evt.index[1] - def get_select_coords(img, evt: gr.SelectData): - return evt.index[1], evt.index[0] + img.select(get_select_coords, [], [w, h]) + predict_mask.click( + get_masked_img, + [img, [w, h]], + [img_with_mask_0, img_with_mask_1, img_with_mask_2] + ) - input_img.select(get_select_coords, [input_img,], [h, w]) if __name__ == "__main__": demo.launch() \ No newline at end of file diff --git a/third_party/lama b/third_party/lama deleted file mode 160000 index 7dee0e4a3cf5f73f86a820674bf471454f52b74f..0000000000000000000000000000000000000000 --- a/third_party/lama +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 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