test

app.py

@@ -0,0 +1,74 @@
+import requests
+import os
+from io import BytesIO
+from PIL import Image
+import numpy as np
+from pathlib import Path
+import gradio as gr
+
+import warnings
+
+warnings.filterwarnings("ignore")
+
+# os.system(
+#     "pip install einops shapely timm yacs tensorboardX ftfy prettytable pymongo click opencv-python inflect nltk scipy scikit-learn pycocotools")
+# os.system("pip install transformers")
+os.system("python setup.py build develop --user")
+
+from maskrcnn_benchmark.config import cfg
+from maskrcnn_benchmark.engine.predictor_glip import GLIPDemo
+
+# Use this command for evaluate the GLIP-T model
+config_file = "configs/pretrain/glip_Swin_T_O365_GoldG.yaml"
+#weight_file = "MODEL/glip_tiny_model_o365_goldg_cc_sbu.pth"
+
+# Use this command if you want to try the GLIP-L model
+# ! wget https://penzhanwu2bbs.blob.core.windows.net/data/GLIPv1_Open/models/glip_large_model.pth -O MODEL/glip_large_model.pth
+# config_file = "configs/pretrain/glip_Swin_L.yaml"
+# weight_file = "MODEL/glip_large_model.pth"
+
+# update the config options with the config file
+# manual override some options
+#cfg.local_rank = 0
+#cfg.num_gpus = 1
+cfg.merge_from_file(config_file)
+#cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
+#cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
+
+glip_demo = GLIPDemo(
+    cfg,
+    min_image_size=800,
+    confidence_threshold=0.7,
+    show_mask_heatmaps=False
+)
+
+
+def predict(image, text):
+    result, _ = glip_demo.run_on_web_image(image[:, :, [2, 1, 0]], text, 0.5)
+    return result[:, :, [2, 1, 0]]
+
+
+image = gr.inputs.Image()
+
+gr.Interface(
+    description="Object Detection in the Wild through GLIP (https://github.com/microsoft/GLIP).",
+    fn=predict,
+    inputs=["image", "text"],
+    outputs=[
+        gr.outputs.Image(
+            type="pil",
+            # label="grounding results"
+        ),
+    ],
+    examples=[
+        ["./flickr_9472793441.jpg", "bobble heads on top of the shelf ."],
+        ["./flickr_9472793441.jpg", "sofa . remote . dog . person . car . sky . plane ."],
+        ["./coco_000000281759.jpg", "A green umbrella. A pink striped umbrella. A plain white umbrella."],
+        ["./coco_000000281759.jpg", "a flowery top. A blue dress. An orange shirt ."],
+        ["./coco_000000281759.jpg", "a car . An electricity box ."],
+        ["./flickr_7520721.jpg", "A woman figure skater in a blue costume holds her leg by the blade of her skate ."]
+    ],
+    article=Path("docs/intro.md").read_text()
+).launch()
+# ).launch(server_name="0.0.0.0", server_port=7000, share=True)
+

main.py

@@ -57,7 +57,7 @@ def run():
 
     demo.launch(server_name=LOCALHOST_NAME, server_port=get_first_available_port(
             INITIAL_PORT_VALUE, INITIAL_PORT_VALUE + TRY_NUM_PORTS
-        )
+        ))
     #demo.launch(server_name="0.0.0.0", server_port=7861)