first commit

app.py

@@ -0,0 +1,42 @@
+import os
+import gradio as gr
+from ultralytics import YOLO
+import numpy as np
+
+model = YOLO('./model/xViewyolov8m_v8_100e.pt')
+example_list = [["examples/" + example] for example in os.listdir("examples")]
+
+
+
+def process_image(input_image):
+ #   results = model(input_image)
+ #   results = model.predict(input_image, conf=0.6, classes=range(0, 78))     
+    results = model.predict(input_image, conf=0.6)
+    class_counts = {}
+    class_counts_str = "Class Counts:\n"
+
+    for r in results:
+        im_array = r.plot()
+        im_array = im_array.astype(np.uint8)
+
+        for box in r.boxes:
+            class_name = r.names[box.cls[0].item()]
+            class_counts[class_name] = class_counts.get(class_name, 0) + 1
+
+        for cls, count in class_counts.items():
+            class_counts_str += f"\n{cls}: {count}"
+
+        return im_array, class_counts_str
+
+iface = gr.Interface(
+    fn=process_image,
+    inputs=gr.Image(),
+    outputs=["image", gr.Textbox(label="More info")],
+    title="YOLO Object detection. Trained on xView dataset. Medium model. Predict with conf=0.6",
+    description='''The xView dataset is composed of satellite images collected from WorldView-3 satellites at a 0.3m ground sample distance.\n 
+                   It contains over 1 million objects across 60 classes in over 1,400 km of imagery.''',
+    live=True,
+    examples=example_list
+    )
+
+iface.launch()

convert_to_jpg.py

@@ -0,0 +1,25 @@
+from PIL import Image
+import os
+
+def convert_tiff_to_jpeg(tiff_path, jpeg_path):
+    try:
+        with Image.open(tiff_path) as img:
+            img.convert('RGB').save(jpeg_path, 'JPEG')
+        print(f"converted: {tiff_path} -> {jpeg_path}")
+    except Exception as e:
+        print(f"error converted {tiff_path}: {e}")
+
+def batch_convert_tiff_to_jpeg(input_folder, output_folder):
+    if not os.path.exists(output_folder):
+        os.makedirs(output_folder)
+
+    for filename in os.listdir(input_folder):
+        if filename.endswith('.tif') or filename.endswith('.tiff'):
+            tiff_path = os.path.join(input_folder, filename)
+            jpeg_path = os.path.join(output_folder, filename.split('.')[0] + '.jpg')
+            convert_tiff_to_jpeg(tiff_path, jpeg_path)
+
+input_folder = './examples'
+output_folder = './examples2'
+
+batch_convert_tiff_to_jpeg(input_folder, output_folder)

requirements.txt

@@ -0,0 +1,5 @@
+gradio==3.49.0
+numpy==1.26.0
+opencv-python==4.9.0.80
+ultralytics==8.1.10
+mediapipe==0.10.7