Delete utils_inference.py

utils_inference.py

@@ -1,119 +0,0 @@
-import numpy as np
-import gradio as gr
-from PIL import ImageDraw
-
-from tools_gradio import fast_process
-from tools import format_results, box_prompt, point_prompt, text_prompt
-
-
-def segment_everything(
-        model,
-        device,
-        input,
-        input_size=1024,
-        iou_threshold=0.7,
-        conf_threshold=0.25,
-        better_quality=False,
-        withContours=True,
-        use_retina=True,
-        text="",
-        wider=False,
-        mask_random_color=True,
-):
-    input_size = int(input_size)
-    w, h = input.size
-    scale = input_size / max(w, h)
-    new_w = int(w * scale)
-    new_h = int(h * scale)
-    input = input.resize((new_w, new_h))
-
-    results = model(input,
-                    device=device,
-                    retina_masks=True,
-                    iou=iou_threshold,
-                    conf=conf_threshold,
-                    imgsz=input_size, )
-
-    if len(text) > 0:
-        results = format_results(results[0], 0)
-        annotations, _ = text_prompt(results, text, input, device=device, wider=wider)
-        annotations = np.array([annotations])
-    else:
-        annotations = results[0].masks.data
-
-    fig = fast_process(annotations=annotations,
-                       image=input,
-                       device=device,
-                       scale=(1024 // input_size),
-                       better_quality=better_quality,
-                       mask_random_color=mask_random_color,
-                       bbox=None,
-                       use_retina=use_retina,
-                       withContours=withContours, )
-    return fig
-
-
-def segment_with_points(
-        model,
-        device,
-        input,
-        input_size=1024,
-        iou_threshold=0.7,
-        conf_threshold=0.25,
-        better_quality=False,
-        withContours=True,
-        use_retina=True,
-        mask_random_color=True,
-):
-    global global_points
-    global global_point_label
-
-    input_size = int(input_size)
-    w, h = input.size
-    scale = input_size / max(w, h)
-    new_w = int(w * scale)
-    new_h = int(h * scale)
-    input = input.resize((new_w, new_h))
-
-    scaled_points = [[int(x * scale) for x in point] for point in global_points]
-
-    results = model(input,
-                    device=device,
-                    retina_masks=True,
-                    iou=iou_threshold,
-                    conf=conf_threshold,
-                    imgsz=input_size, )
-
-    results = format_results(results[0], 0)
-    annotations, _ = point_prompt(results, scaled_points, global_point_label, new_h, new_w)
-    annotations = np.array([annotations])
-
-    fig = fast_process(annotations=annotations,
-                       image=input,
-                       device=device,
-                       scale=(1024 // input_size),
-                       better_quality=better_quality,
-                       mask_random_color=mask_random_color,
-                       bbox=None,
-                       use_retina=use_retina,
-                       withContours=withContours, )
-
-    global_points = []
-    global_point_label = []
-    return fig, None
-
-
-def get_points_with_draw(image, label, evt: gr.SelectData):
-    global global_points
-    global global_point_label
-
-    x, y = evt.index[0], evt.index[1]
-    point_radius, point_color = 15, (255, 255, 0) if label == 'Add Mask' else (255, 0, 255)
-    global_points.append([x, y])
-    global_point_label.append(1 if label == 'Add Mask' else 0)
-
-    print(x, y, label == 'Add Mask')
-
-    draw = ImageDraw.Draw(image)
-    draw.ellipse([(x - point_radius, y - point_radius), (x + point_radius, y + point_radius)], fill=point_color)
-    return image