Spaces:
Runtime error
Runtime error
File size: 1,498 Bytes
404e97e e7d6ec4 404e97e 254a800 404e97e 254a800 404e97e cd05082 0ebcebc 404e97e 254a800 404e97e 6088e85 e3f8504 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
from gradio.outputs import Label
from icevision.all import *
from icevision.models.checkpoint import *
import PIL
import gradio as gr
import os
# Load model new
checkpoint_path = "model_checkpoint.pth"
checkpoint_and_model = model_from_checkpoint(checkpoint_path)
model = checkpoint_and_model["model"]
model_type = checkpoint_and_model["model_type"]
class_map = checkpoint_and_model["class_map"]
# Transforms
img_size = checkpoint_and_model["img_size"]
valid_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(img_size), tfms.A.Normalize()])
examples = [['1.jpg'],['2.jpg'],['3.jpg']]
def show_preds(input_image):
img = PIL.Image.fromarray(input_image, "RGB")
pred_dict = model_type.end2end_detect(img, valid_tfms, model, class_map=class_map, detection_threshold=0.5,
display_label=False, display_bbox=True, return_img=True,
font_size=16, label_color="#FF59D6")
return pred_dict["img"], len(pred_dict["detection"]["bboxes"])
gr_interface = gr.Interface(
fn=show_preds,
inputs=["image"],
outputs=[gr.outputs.Image(type="pil", label=" Inference"), gr.outputs.Textbox(type="number", label="Count")],
title="Detector",
description="This model counts on a given image. Upload an image or click an example image below to use.",
article="",
examples=examples,
theme="dark-grass",
enable_queue=True
)
gr_interface.launch()
#7 |