init commit

.idea/detector.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.9 (detector)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (detector)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/detector.iml" filepath="$PROJECT_DIR$/.idea/detector.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

.idea/workspace.xml

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+<?xml version="1.0" encoding="UTF-8"?>
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+      <change afterPath="$PROJECT_DIR$/main.py" afterDir="false" />
+      <change afterPath="$PROJECT_DIR$/model.py" afterDir="false" />
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+      <list>
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+        <option value="FastAPI test_main" />
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+  <component name="Git.Settings">
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+    <option name="showLibraryContents" value="true" />
+  </component>
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+    &quot;RunOnceActivity.OpenProjectViewOnStart&quot;: &quot;true&quot;,
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+    &quot;node.js.detected.package.tslint&quot;: &quot;true&quot;,
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+    &quot;node.js.selected.package.tslint&quot;: &quot;(autodetect)&quot;,
+    &quot;nodejs_package_manager_path&quot;: &quot;npm&quot;,
+    &quot;vue.rearranger.settings.migration&quot;: &quot;true&quot;
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+}</component>
+  <component name="RecentsManager">
+    <key name="CopyFile.RECENT_KEYS">
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+      <option name="ENV_FILES" value="" />
+      <option name="INTERPRETER_OPTIONS" value="" />
+      <option name="PARENT_ENVS" value="true" />
+      <envs>
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+      <option name="SDK_HOME" value="" />
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+      <option name="ADD_CONTENT_ROOTS" value="true" />
+      <option name="ADD_SOURCE_ROOTS" value="true" />
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+      <option name="EMULATE_TERMINAL" value="false" />
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+      <option name="REDIRECT_INPUT" value="false" />
+      <option name="INPUT_FILE" value="" />
+      <method v="2" />
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+    <configuration name="detector" type="Python.FastAPI">
+      <option name="file" value="$PROJECT_DIR$/main.py" />
+      <module name="detector" />
+      <option name="ENV_FILES" value="" />
+      <option name="INTERPRETER_OPTIONS" value="" />
+      <option name="PARENT_ENVS" value="true" />
+      <option name="SDK_HOME" value="" />
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+      <option name="IS_MODULE_SDK" value="false" />
+      <option name="ADD_CONTENT_ROOTS" value="true" />
+      <option name="ADD_SOURCE_ROOTS" value="true" />
+      <EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
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+      <method v="2" />
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+      <option name="number" value="Default" />
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+    <servers />
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+  <component name="TypeScriptGeneratedFilesManager">
+    <option name="version" value="3" />
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+  <component name="com.intellij.coverage.CoverageDataManagerImpl">
+    <SUITE FILE_PATH="coverage/detector$demo.coverage" NAME="demo Coverage Results" MODIFIED="1702302380580" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$" />
+  </component>
+</project>

Dockerfile

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+FROM python:bookworm
+
+WORKDIR /app
+COPY . /app
+RUN pip install -r requirements.txt
+ENTRYPOINT ["streamlit", "run", "demo.py"]

README.md

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+---
+title: Object Detector
+emoji: 🚀
+colorFrom: yellow
+colorTo: yellow
+sdk: docker
+pinned: false
+license: apache-2.0
+app_port: 8501
+---

demo.py

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+
+import time
+from PIL import Image
+import streamlit as st
+
+from model import detect
+
+
+def main():
+    # Header & Page Config.
+    st.set_page_config(
+        page_title="Parth - Detr",
+        layout="centered")
+    st.title("Object Detection using DETR:")
+
+    # This will let you upload PNG, JPG & JPEG File
+    buffer = st.file_uploader("Upload your Image here", type=["jpg", "png", "jpeg"])
+
+    if buffer:
+        # Object Detecting
+        with st.spinner('Wait for it...'):
+            # Slider for changing confidence
+            confidence = st.slider('Confidence Threshold', 0, 100, 90)
+
+            # Calculating time for detection
+            t1 = time.time()
+            im = Image.open(buffer)
+            # im.save("saved_images/image.jpg")
+            res_img = detect(im, confidence)
+            t2 = time.time()
+
+        # Displaying the image
+        st.image(res_img, use_column_width=True)
+
+        # Printing Time
+        st.write("\n")
+        st.write("Time taken: ", t2 - t1, "sec.")
+
+
+if __name__ == '__main__':
+    main()

main.py

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+from fastapi import FastAPI
+
+app = FastAPI()
+
+
+@app.get("/")
+async def root():
+    return {"message": "Hello World"}
+
+
+@app.get("/hello/{name}")
+async def say_hello(name: str):
+    return {"message": f"Hello {name}"}

model.py

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+
+import cv2
+import torch
+import random
+from PIL import ImageDraw
+import torchvision.transforms as T
+
+# COCO Classes
+CLASSES = [
+    'N/A', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus',
+    'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'N/A',
+    'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse',
+    'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'N/A', 'backpack',
+    'umbrella', 'N/A', 'N/A', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis',
+    'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove',
+    'skateboard', 'surfboard', 'tennis racket', 'bottle', 'N/A', 'wine glass',
+    'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich',
+    'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake',
+    'chair', 'couch', 'potted plant', 'bed', 'N/A', 'dining table', 'N/A',
+    'N/A', 'toilet', 'N/A', 'tv', 'laptop', 'mouse', 'remote', 'keyboard',
+    'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'N/A',
+    'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier',
+    'toothbrush'
+]
+
+# Standard PyTorch mean-std Input Image Normalization
+transform = T.Compose([
+    T.Resize(500),
+    T.ToTensor(),
+    T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+])
+
+
+# For Output Bounding Box Post-processing
+def box_cxcywh_to_xyxy(x):
+    x_c, y_c, w, h = x.unbind(1)
+    b = [(x_c - 0.5 * w), (y_c - 0.5 * h),
+         (x_c + 0.5 * w), (y_c + 0.5 * h)]
+    return torch.stack(b, dim=1)
+
+
+def rescale_bboxes(out_bbox, size):
+    img_w, img_h = size
+    b = box_cxcywh_to_xyxy(out_bbox)
+    b = b * torch.tensor([img_w, img_h, img_w, img_h], dtype=torch.float32)
+    return b
+
+
+# Pre-processing on Image
+def image_processing(im, model, transform, confidence=0.9):
+    # im = Image.open(image_path)
+    img = transform(im).unsqueeze(0)
+
+    outputs = model(img)
+    probas = outputs['pred_logits'].softmax(-1)[0, :, :-1]
+    keep = probas.max(-1).values > confidence
+    bboxes_scaled = rescale_bboxes(outputs['pred_boxes'][0, keep], im.size)
+
+    return probas[keep], bboxes_scaled
+
+
+# Helper Functions for Plotting BBoxes
+def plot_one_box(x, img, color=None, label=None, line_thickness=None):
+    width, height = img.size
+    tl = line_thickness or round(0.002 * (width + height) / 2) + 1  # line/font thickness
+    color = color or (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
+    c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3]))
+    img_draw = ImageDraw.Draw(img)
+    img_draw.rectangle((c1[0], c1[1], c2[0], c2[1]), outline=color, width=tl)
+    if label:
+        tf = max(tl - 1, 1)  # font thickness
+        t_size = cv2.getTextSize(label, 0, fontScale=tl / 5, thickness=tf)[0]
+        c2 = c1[0] + t_size[0], c1[1] + t_size[1] - 3
+        img_draw.rectangle((c1, c2), fill=color)
+        img_draw.text((c1[0], c1[1] - 2), label, fill=(255, 255, 255))
+
+
+# Ploting Bounding Box on img
+def add_bboxes(pil_img, prob, bboxes):
+    for p, coord in zip(prob, bboxes.tolist()):
+        cl = p.argmax()
+        text = f'{CLASSES[cl]}: {p[cl]: 0.2f}'
+        plot_one_box(x=coord, img=pil_img, label=text)
+
+    return pil_img
+
+
+def detect(im, confidence):
+    # Load model
+    model = torch.hub.load('facebookresearch/detr', 'detr_resnet101', pretrained=True)
+    model.eval()
+
+    scores, boxes = image_processing(im, model, transform, confidence / 100)
+    # im = cv2.imread(image_path)
+    # im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
+    im = add_bboxes(im, scores, boxes)
+
+    return im

requirements.txt

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+altair==5.2.0
+annotated-types==0.6.0
+anyio==3.7.1
+attrs==23.1.0
+blinker==1.7.0
+cachetools==5.3.2
+certifi==2023.11.17
+charset-normalizer==3.3.2
+click==8.1.7
+exceptiongroup==1.2.0
+fastapi==0.104.1
+filelock==3.13.1
+fsspec==2023.12.1
+gitdb==4.0.11
+GitPython==3.1.40
+h11==0.14.0
+httptools==0.6.1
+idna==3.6
+importlib-metadata==6.11.0
+Jinja2==3.1.2
+jsonschema==4.20.0
+jsonschema-specifications==2023.11.2
+markdown-it-py==3.0.0
+MarkupSafe==2.1.3
+mdurl==0.1.2
+mpmath==1.3.0
+networkx==3.2.1
+numpy==1.26.2
+opencv-python==4.8.1.78
+packaging==23.2
+pandas==2.1.4
+Pillow==10.1.0
+protobuf==4.25.1
+pyarrow==14.0.1
+pydantic==2.5.2
+pydantic_core==2.14.5
+pydeck==0.8.1b0
+Pygments==2.17.2
+python-dateutil==2.8.2
+python-dotenv==1.0.0
+pytz==2023.3.post1
+PyYAML==6.0.1
+referencing==0.32.0
+requests==2.31.0
+rich==13.7.0
+rpds-py==0.13.2
+scipy==1.11.4
+six==1.16.0
+smmap==5.0.1
+sniffio==1.3.0
+starlette==0.27.0
+streamlit==1.29.0
+sympy==1.12
+tenacity==8.2.3
+toml==0.10.2
+toolz==0.12.0
+torch==2.1.0
+torchaudio==2.1.0
+torchvision==0.16.1
+tornado==6.4
+typing_extensions==4.9.0
+tzdata==2023.3
+tzlocal==5.2
+urllib3==2.1.0
+uvicorn==0.24.0.post1
+uvloop==0.19.0
+validators==0.22.0
+watchfiles==0.21.0
+websockets==12.0
+zipp==3.17.0